Quercetin and kaempferol increase the intestinal absorption of isorhamnetin coexisting in Elaeagnus rhamnoides (L.) A. Nelson (Elaeagnaceae) extracts via regulating multidrug resistance-associated protein 2.

BACKGROUND: Isorhamnetin (IS) is a flavonoid component with many biological activities such as antioxidant, anti-inflammatory, and anticancer, which is also the main active component in total flavones of Elaeagnus rhamnoides (L.) A. Nelson (Elaeagnaceae) (TFH); however, the interaction between IS and other components in TFH is unclear. PURPOSE: The aim of the present study was to investigate the enhancement of quercetin (QU) or kaempferol (KA) on the intestinal absorption of IS coexisting in TFH, and then preliminarily illuminate the related mechanisms. METHODS: Firstly, the intestinal absorption of IS in the presence or absence of QU or KA was conducted by in vivo pharmacokinetics model, in situ single-pass intestinal perfusion model (SPIP), and MDCK II-MRP2 monolayer cell model to confirm the enhancement of QU or KA on IS absorption. Secondly, the effects of multidrug resistance-associated protein 2 (MRP2) inhibitors on the IS intestinal absorption were investigated to ascertain the mediation of MRP2 on IS absorption. Finally, the effects of QU or KA on MRP2 activity, protein expression, and mRNA level were performed by SPIP, everted-gut sacs, western blotting, and real-time polymerase chain reaction experiments to elucidate the related mechanisms. RESULTS: QU or KA increased IS intestinal absorption according to the increased AUC0-96h, Cmax, and Peff of IS after co-administrated with QU or KA to rats; the oral absorption of IS was mediated by MRP2 based on the facts that the average plasma concentration, AUC0-96h, and Peff of IS were increased when co-administrated with PR or MK571 (MRP2 inhibitors) as well as the Pratio(BL/AP) of IS was decreased by MK571 in MDCK II-MRP2 cell monolayer; the activity, protein expression, and mRNA level of MRP2 were inhibited or down-regulated by QU or KA because of the increased Peff of MRP2 substrate calcein (CA) and the down-regulated relative protein and mRNA intensity after co-treated with QU or KA. CONCLUSION: QU and KA increased the intestinal absorption of IS in TFH by regulating the activity and expression of MRP2, which provides useful information for the investigation of the transporter-mediated interaction of flavonoid components in herbal extracts.

The intestinal absorption properties of flavonoids in Hippophaë rhamnoides extracts by an in situ single-pass intestinal perfusion model.

The purpose of this study was to investigate the absorption properties of isorhamnetin (IS), quercetin (QU), and kaempferol (KA) in total flavones of Hippophaë rhamnoides L. (TFH) by an in situ single-pass intestinal perfusion model. The results indicated that IS, QU, and KA in TFH were absorbed site-dependently, and both enterohepatic circulation and intestinal flora could participate in their absorption processes. The absorption mechanisms of IS, QU, and KA in TFH were involved in both passive diffusion and active transport, and the mediation of efflux transporter multidrug resistance-associated proteins (MRPs) should not be neglected.

A Network Pharmacology Approach to Uncover the Molecular Mechanisms of Herbal Formula Ban-Xia-Xie-Xin-Tang.

Ban-Xia-Xie-Xin-Tang (BXXXT) is a classical formula from Shang-Han-Lun which is one of the earliest books of TCM clinical practice. In this work, we investigated the therapeutic mechanisms of BXXXT for the treatment of multiple diseases using a network pharmacology approach. Here three BXXXT representative diseases (colitis, diabetes mellitus, and gastric cancer) were discussed, and we focus on in silico methods that integrate drug-likeness screening, target prioritizing, and multilayer network extending. A total of 140 core targets and 72 representative compounds were finally identified to elucidate the pharmacology of BXXXT formula. After constructing multilayer networks, a good overlap between BXXXT nodes and disease nodes was observed at each level, and the network-based proximity analysis shows that the relevance between the formula targets and disease genes was significant according to the shortest path distance (SPD) and a random walk with restart (RWR) based scores for each disease. We found that there were 22 key pathways significantly associated with BXXXT, and the therapeutic effects of BXXXT were likely addressed by regulating a combination of targets in a modular pattern. Furthermore, the synergistic effects among BXXXT herbs were highlighted by elucidating the molecular mechanisms of individual herbs, and the traditional theory of "Jun-Chen-Zuo-Shi" of TCM formula was effectively interpreted from a network perspective. The proposed approach provides an effective strategy to uncover the mechanisms of action and combinatorial rules of BXXXT formula in a holistic manner.

Development of in Silico Models for Predicting P-Glycoprotein Inhibitors Based on a Two-Step Approach for Feature Selection and Its Application to Chinese Herbal Medicine Screening.

P-glycoprotein (P-gp) is regarded as an important factor in determining the ADMET (absorption, distribution, metabolism, elimination, and toxicity) characteristics of drugs and drug candidates. Successful prediction of P-gp inhibitors can thus lead to an improved understanding of the underlying mechanisms of both changes in the pharmacokinetics of drugs and drug-drug interactions. Therefore, there has been considerable interest in the development of in silico modeling of P-gp inhibitors in recent years. Considering that a large number of molecular descriptors are used to characterize diverse structural moleculars, efficient feature selection methods are required to extract the most informative predictors. In this work, we constructed an extensive available data set of 2428 molecules that includes 1518 P-gp inhibitors and 910 P-gp noninhibitors from multiple resources. Importantly, a two-step feature selection approach based on a genetic algorithm and a greedy forward-searching algorithm was employed to select the minimum set of the most informative descriptors that contribute to the prediction of P-gp inhibitors. To determine the best machine learning algorithm, 18 classifiers coupled with the feature selection method were compared. The top three best-performing models (flexible discriminant analysis, support vector machine, and random forest) and their ensemble model using respectively only 3, 9, 7, and 14 descriptors achieve an overall accuracy of 83.2%-86.7% for the training set containing 1040 compounds, an overall accuracy of 82.3%-85.5% for the test set containing 1039 compounds, and a prediction accuracy of 77.4%-79.9% for the external validation set containing 349 compounds. The models were further extensively validated by DrugBank database (1890 compounds). The proposed models are competitive with and in some cases better than other published models in terms of prediction accuracy and minimum number of descriptors. Applicability domain then was addressed by developing an ensemble classification model to obtain more reliable predictions. Finally, we employed these models as a virtual screening tool for identifying potential P-gp inhibitors in Traditional Chinese Medicine Systems Pharmacology (TCMSP) database containing a total of 13 051 unique compounds from 498 herbs, resulting in 875 potential P-gp inhibitors and 15 inhibitor-rich herbs. These predictions were partly supported by a literature search and are valuable not only to develop novel P-gp inhibitors from TCM in the early stages of drug development, but also to optimize the use of herbal remedies.

Teng-Long-Bu-Zhong-Tang, a Chinese herbal formula, enhances anticancer effects of 5--Fluorouracil in CT26 colon carcinoma.

BACKGROUND: Colorectal cancer remains one of the leading causes of cancer death worldwide. Traditional Chinese Medicine (TCM) has played a positive role in colorectal cancer treatment. There is a great need to establish effective herbal formula for colorectal cancer treatment. Based on TCM principles and clinical practices, we have established an eight herbs composed formula for colorectal cancer treatment, which is Teng-Long-Bu-Zhong-Tang (TLBZT). We have demonstrated the anticancer effects of TLBZT against colorectal carcinoma in vitro. In present study, we evaluated the anticancer potential of TLBZT, used alone or in combination with low dose of 5-Fluorouracil (5-Fu), in CT26 colon carcinoma in vivo. METHODS: CT26 colon carcinoma was established in BALB/c mice and treated with TLBZT, 5-Fu, or TLBZT plus 5-Fu. The tumor volumes were observed. Apoptosis was detected by TUNEL assay. Caspases activities were detected by colorimetric assay. Cell senescence was indentified by senescence ß-galactosidase staining. Gene expression and angiogenesis was observed by immunohistochemistry or western blot. RESULTS: TLBZT significantly inhibited CT26 colon carcinoma growth. TLBZT elicited apoptosis in CT26 colon carcinoma, accompanied by Caspase-3, 8, and 9 activation and PARP cleavage, and downregulation of XIAP and Survivin. TLBZT also induced cell senescence in CT26 colon carcinoma, with concomitant upregulation of p16 and p21 and downregulation of RB phosphorylation. In addition, angiogenesis and VEGF expression in CT26 colon carcinoma was significantly inhibited by TLBZT treatment. Furthermore, TLBZT significantly enhanced anticancer effects of 5-Fu in CT26 colon carcinoma. CONCLUSIONS: TLBZT exhibited significantly anticancer effect, and enhanced the effects of 5-Fu in CT26 colon carcinoma, which may correlate with induction of apoptosis and cell senescence, and angiogenesis inhibition. The present study provides new insight into TCM approaches for colon cancer treatment that are worth of further study.

[Effect of Solanum nigrum on human colon carcinoma RKO cells ].

OBJECTIVE: To evaluate the effect of Solanum nigrum on adhesion, migration and invasion in human colon carcinoma RKO cells. METHODS: RKO cells were treated with different dose of Solanum nigrum. Cell proliferation was detected by CCK-8 assay. Cell adhesion was observed with CytoSelect 48-Well Cell Adhesion Assay. Cell migration was detected with scratch assay. Cell invasion was analyzed by CytoSelect 24-Well Cell Invasion Assay. RESULTS: At final concentration of 400-1600 microg/mL, Solanum nigrum significantly inhibited proliferation of RKO cells in a dose-dependent manner. At final concentration of 100-400 microg/mL, Solanum nigrum significantly inhibited adhesion,migration and invasion in RKO cells. CONCLUSION: Solanum nigrum may inhibit the proliferation, adhesion, migration and invasive abilities in RKO cells. The present study provides new insight into the application of Solanum nigrum for colon carcinoma treatment that are worthy of further study.

[Application of genetic algorithm in blending technology for extractions of Cortex Fraxini].

OBJECTIVE: To explore the feasibility of genetic algorithm (GA) on multiple objective blending technology for extractions of Cortex Fraxini. METHOD: According to that the optimization objective was the combination of fingerprint similarity and the root-mean-square error of multiple key constituents, a new multiple objective optimization model of 10 batches extractions of Cortex Fraxini was built. The blending coefficient was obtained by genetic algorithm. The quality of 10 batches extractions of Cortex Fraxini that after blending was evaluated with the finger print similarity and root-mean-square error as indexes. RESULT: The quality of 10 batches extractions of Cortex Fraxini that after blending was well improved. Comparing with the fingerprint of the control sample, the similarity was up, but the degree of variation is down. The relative deviation of the key constituents was less than 10%. CONCLUSION: It is proved that genetic algorithm works well on multiple objective blending technology for extractions of Cortex Fraxini. This method can be a reference to control the quality of extractions of Cortex Fraxini. Genetic algorithm in blending technology for extractions of Chinese medicines is advisable.

[Experimental study on electroacupuncture for strengthening gastrointestinal motility in the rat with acute pancreatitis].

OBJECTIVE: To explore the mechanism of EA in treatment of acute pancreatitis. METHODS: Twenty-four healthy male Wistar rats were randomly divided into 3 groups, a control group, a model group and an EA group. In the model group, rat acute pancreatitis model was prearpared by intraperitoneal injection of Caerulein, and in the EA group, EA was given at "Zusanli" (ST 36) and "Tianshu" (ST 25) of the model rat. The gastric emptying rate, small intestinal impelling ratio, myeloperoxidase activity in the pancreas tissue, pathological score of the pancreas and serum amylase were detected. RESULTS: Compared with the control group, both the gastric emptying rate and the intestinal impelling ratio significantly decreased in the model group (P<0.05), and they significantly increased in the EA group compared with the model group (P<0.05). Myeloperoxidase activity in the pancreas tissue, pathological score of the pancreas and serum amylase activity significantly decreased in the EA group as compared with the model group (P<0.05). CONCLUSION: EA can significantly improve the disturbance of gastrointestinal motility induced by acute pancreatitis and relieve pathological damage of pancreas.

[Back-propagation neural network and genetic algorithm for multi-objective optimization of extraction technology of Cortex Fraxini].

OBJECTIVE: To introduce Back-propagation (BP) neural network and genetic algorithm for multi-objective optimization of extraction technology of Cortex Fraxini. METHOD: BP neural network was established and optimized with uniform design. Genetic algotithm was used for multi-objective optimization of extraction technology of cortex fraxini. RESULT: the optimization of extraction was as follows: extraction temperature was 99 degrees C, concentration of EtOH was 50%, liquid-solid ratio was 7, extraction time was 94 min. The proportional error between predictive value and practical measured value was just -1.16% and -5.14%. CONCLUSION: Back-propagation neural network and genetic algorithm for multi-objective optimization of extraction technology of cortex fraxini is advisable.