Effects of flavonoids derived from Taxus yunnanensis on p-glycoprotein and cytochrome P450 3A4

AbstractThe intestinal uptake of paclitaxel is hampered by trans-membrane efflux transporters such as P-glycoprotein (P-gp), and paclitaxel is mainly metabolized by cytochrome P450 3A4 (CYP3A4) presented in the liver. Our previous results demonstrated that flavonoids extracted from Taxus yunnanensis could improve the oral absorption of paclitaxel. The current study was purposed to investigate the effects of the flavonoid extracts on P-gp and CYP3A4 in vitro. The expression and activity of P-gp were detected by western blotting and intracellular rhodamine 123 accumulation assay in Caco-2 cells treated with the flavonoids extract. The expression of CYP3A4 was investigated by western blotting in mouse primary hepatocytes and the activity of CYP3A4 was detected by LC-MS/MS method using rat liver microsomes. Our results showed that the flavonoid extracts from T. yunnanensis could inhibit P-gp activity and concurrently decrease the expression and activity of CYP3A4. In conclusion, activity of P-gp and CYP3A4 could be inhibited by flavonoids extracted from T. yunnanensis which might be potential candidates for development of oral formulation of paclitaxel

Role of curcumin in ischemia and reperfusion injury

Ischemia-reperfusion injury (IRI) is an inevitable pathological process after organic transplantations. Although traditional treatments restore the blood supply of ischemic organs, the damage caused by IRI is always ignored. Therefore, the ideal and effective therapeutic strategy to mitigate IRI is warrented. Curcumin is a type of polyphenols, processing such properties as anti-oxidative stress, anti-inflammation and anti-apoptosis. However, although many researches have been confirmed that curcumin can exert great effects on the mitigation of IRI, there are still some controversies about its underlying mechanisms among these researches. Thus, this review is to summarize the protective role of curcumin against IRI as well as the controversies of current researches, so as to clarify its underlying mechanisms clearly and provide clinicians a novel idea of the therapy for IRI

Multi-View Cluster Analysis With Incomplete Data to Understand Treatment Effects

Multi-view cluster analysis, as a popular granular computing method, aims to partition sample subjects into consistent clusters across different views in which the subjects are characterized. Frequently, data entries can be missing from some of the views. The latest multi-view co-clustering methods cannot effectively deal with incomplete data, especially when there are mixed patterns of missing values. We propose an enhanced formulation for a family of multi-view co-clustering methods to cope with the missing data problem by introducing an indicator matrix whose elements indicate which data entries are observed and assessing cluster validity only on observed entries. In comparison with the simple strategy of removing subjects with missing values, our approach can use all available data in cluster analysis. In comparison with common methods that impute missing data in order to use regular multi-view analytics, our approach is less sensitive to imputation uncertainty. In comparison with other state-of-the-art multi-view incomplete clustering methods, our approach is sensible in the cases of missing any value in a view or missing the entire view, the most common scenario in practice. We first validated the proposed strategy in simulations, and then applied it to a treatment study of heroin dependence which would have been impossible with previous methods due to a number of missing-data patterns. Patients in a treatment study were naturally assessed in different feature spaces such as in the pre-, during-and post-treatment time windows. Our algorithm was able to identify subgroups where patients in each group showed similarities in all of the three time windows, thus leading to the recognition of pre-treatment (baseline) features predictive of post-treatment outcomes

3,3-Dimethyl-1-[5-(1H-1,2,4-triazol-1-yl­meth­yl)-1,3,4-thia­diazol-2-ylsulfan­yl]butan-2-one

In the mol­ecule of the title compound, C11H15N5OS2, the thia­diazole and triazole rings are not coplanar, the dihedral angle formed by their mean planes being 59.9 (2)°. The exocyclic S atom, and the methyl­ene, carbonyl, tert-butyl and one methyl carbon form an approximately planar zigzag chain, which makes a dihedral angle of 74.6 (1)° with the thia­diazole ring