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Elucidating the quality markers(Q-markers) of traditional Chinese medicines is essential for understanding the mechanisms of action and promoting the rational use of traditional Chinese medicines as well as for developing traditional Chinese medicine-derived drugs. Studies have shown that surface plasmon resonance(SPR) is promising in this field. This study proposed a method based on pull-down with SPR chips to predict the Q-markers of Angong Niuhuang pills(AGNHP). Firstly, 71 main chemical components of AGNHP were analyzed by UPLC-Q-TOF-MS, and then network pharmacology was employed to predict the potential targets of AGNHP against stroke. Secondly, the STAT3 protein chip was constructed, and the extract of AGNHP was recovered by pull-down of the SPR system for STAT3 ligand. The potential active ingredients were collected, enriched, and identified as coptisine, palmatine, epiberberine, berberine, worenine, demethyleneberberine, jatrorrhizine, tetrahydrocoptisine, baicalein, and baicalin methyl ester. Next, the affinity constants of the 10 active ingredients were determined as 44.7, 44, 58.1, 51.3, 39.7, 32.1, 49.2, 69.1, 19.7, and 24.9 μmol·L~(-1), respectively. The molecular docking results showed that the 10 compounds could compete for binding with STAT3. This is the first report that SPR combined with UPLC-Q-TOF-MS is reliable and feasible for determining the active ingredients of AGNHP at the molecular level from complex systems. STAT3 could be used as a potential target for the biological quality evaluation of AGNHP.

Objective: To explore the effect of Jianpi Tongluo Jiedu Recipe (JTJR) on protein expression levels of COX-2, NF-kappaBp65, Bcl-2, and Bax, mRNA expression levels of COX-2 and Bcl-2, and the apoptotic index (Al) in gastric mucosa of patients with precancerous lesions of gastric cancer (PL-GC)., Methods: Totally 65 PLGC patients were recruited and treated by JTJR (modified by syndrome typing), one dose per day for six successive months. Protein expression levels of COX-2, NF-KBp65, Bcl-2, and Bax were detected in 65 patients using immunohistochemical (IHC) assay before and after treatment. mRNA expression levels of COX-2 and Bcl-2 were detected in 54 patients using reverse transcription-polymerase chain reaction (RT-PCR). Meanwhile, changes of Al was detected in 65 patients using TdT-mediated dUTP-biotin nick end labeling (TUNEL) fluorescence method., Results: After treatment with JTJR, positive protein expression levels of COX-2, NF-KBp65, and Bcl-2 were obviously decreased in the gastric mucosa of PLGC patients (P <0.01), but Bax positive protein expression was found to be higher (P < 0.05). At the same time mRNA expression levels of COX-2 and Bcl-2 were significantly lower after treatment than before treatment (P < 0.05, P < 0.01); Al also increased after treatment (P < 0.05)., Conclusion: JTJR could promote apoptosis possibly via NF-kappaBp65/COX-2, COX-2/Bcl-2, and NF-kappaBp65/Bcl-2 signaling pathways, thereby affecting PLGC patients.

Objective: To investigate whether the ERK/FoxO3a signal axis could induce the inhibitory effect of vitexin 1 (VB-1) in HepG2 cell proliferation., Method: The MTT method was adopted to observe the effect of different concentrations of VB-1 on human hepatoma carcinoma cell line HepG2 and immortalized human embryo liver cell line L-02. The cell growth was assessed by the clone formation assay. The protein phosphorylation levels of ERK1/2 and FoxO3a were measured by the western blot., Result: VB-1 inhibited the viability of HepG2 cell line in a concentration-dependent manner, with a weak effect on L-02 cell line. VB-1 could effectively inhibit the anchorage-dependent growth of HepG2 cells, and reduce the expression levels of pERK1/2 and pFoxO3a in a concentration-dependent manner. MEK1/2 inhibitor PD98059 could enhance VB-1' s effect in inhibiting HepG2 cell proliferation and ERK1/2, FoxO3a phosphorylation., Conclusion: VB-1 inhibits the proliferative activity of hepatoma carcinoma cell line HepG2 by blocking the ERK/FoxO3a signal axis.

Chinese medicine (CM) is a discipline with its own distinct methodologies and philosophical principles. The main method of treatment in CM is to use herbal prescriptions. Typically, a number of herbs are combined to form a formula and different formulae are prescribed for different patients. Regularities in the mixture of herbs in the prescriptions are important for both clinical treatment and novel patent medicine development. In this study, we analyze CM formula data using latent tree (LT) models. Interesting regularities are discovered. Those regularities are of interest to students of CM as well as pharmaceutical companies that manufacture medicine using Chinese herbs.

Objective: To explore the most effective herbal combinations commonly used by highly experienced Chinese medicine (CM) physicians for the treatment of insomnia., Methods: We collected and analyzed data related to insomnia treatment from the clinics of 7 highly experienced CM physicians in Beijing. The sample included 162 patients and 460 consultations in total. Patient outcomes, such as sleep quality and sleep time per day, were manually collected from the medical records by trained CM clinicians. Three data mining methods, support vector machine (SVM), logistic regression and decision tree, and multifactor dimensionality reduction (MDR), were used to determine and confirm the herbal combinations that resulted in positive outcomes in patients suffering from insomnia., Results: Results show that MDR is the most efficient method to predict the effective herbal combinations. Using the MDR model, we identified several combinations of herbs with 100% positive outcomes, such as stir-fried spine date seed, Szechwan lovage rhizome, and prepared thinleaf milkwort root; white peony root, golden thread, and stir-fried spine date seed; and Asiatic cornelian cherry fruit with fresh rehmannia., Conclusions: Results indicate that herbal combinations are effective treatments for patients with insomnia compared with individual herbs. It is also shown that MDR is a potent data mining method to identify the herbal combination with high rates of positive outcome.

Objective: To find an appropriate feature representation in the biclustering of symptom-herb relationship in Chinese medicine (CM)., Methods: Four different representation schemes were tested in identifying the complex relationship between symptoms and herbs using a biclustering algorithm on an insomnia data set. These representation schemes were effective count, binary value, relative success ratio, or modified relative success ratio. The comparison of the schemes was made on the number and size of biclusters with respect to different threshold values., Results and Conclusions: The modified relative success ratio scheme was the most appropriate feature representation among the four tested. Some of the biclusters selected from this representation scheme were known to follow the therapeutic principles of CM, while others may offer clues for further clinical investigations.