Effect of Radix Platycodonis and Radix Cyathulae in Xuefu Zhuyu Tang on tissuedistribution of paeoniflorin in blood-stasis mice by HPLC: Experimentalevidence on Shi ingredients in traditional formula compatibility

Xuefu Zhuyu Tang (XFZY), a famous formula in traditional Chinese medicine, has been demonstrated to show goodtherapeutic effects on diseases caused by blood stasis syndrome. Two of its eleven herbs, Radix Platycodonis and RadixCyathulae, have been considered as Shi ingredients in the hierarchy of traditional formula compatibility and provenpossessing synergistic properties that strengthen the formula's potency of activating blood circulation and resolving bloodstagnation. However, its mechanism is still not clearly elucidated. In our previous study, we observed their effects onpaeoniflorin pharmacokinetics of XFZY in rats. In this study, we continued by detecting and comparing their effect on thetissue distribution of paeoniflorin after oral administration of XFZY and its three variants (XFZY without RadixPlatycodonis or/and Radix Cyathulae) in blood-stasis mice via HPLC assay. The results indicated that combining usage ofRadix Platycodonis and Radix Cyathula increased the distribution of paeoniflorin in the lung and kidney and introduced thepaeoniflorin into the liver, spleen and heart. It might explain their synergistic properties that strengthen the formula's effectof invigorating blood and dissolving stasis and provide experimental evidence to understand the pharmacological effects ofShi herbs in the hierarchy of traditional formula compatibility

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies

Molecular characterization and clinical relevance of metabolic expression subtypes in human cancers.

Metabolic reprogramming provides critical information for clinical oncology. Using molecular data of 9,125 patient samples from The Cancer Genome Atlas, we identified tumor subtypes in 33 cancer types based on mRNA expression patterns of seven major metabolic processes and assessed their clinical relevance. Our metabolic expression subtypes correlated extensively with clinical outcome: subtypes with upregulated carbohydrate, nucleotide, and vitamin/cofactor metabolism most consistently correlated with worse prognosis, whereas subtypes with upregulated lipid metabolism showed the opposite. Metabolic subtypes correlated with diverse somatic drivers but exhibited effects convergent on cancer hallmark pathways and were modulated by highly recurrent master regulators across cancer types. As a proof-of-concept example, we demonstrated that knockdown of SNAI1 or RUNX1—master regulators of carbohydrate metabolic subtypes-modulates metabolic activity and drug sensitivity. Our study provides a system-level view of metabolic heterogeneity within and across cancer types and identifies pathway cross-talk, suggesting related prognostic, therapeutic, and predictive utility

Time varying prediction of UK asset returns

This paper studies the economic significance of stock and bond return predictability in UK market over period February 1991 to May 2002, based on a real-time investment simulation with only publicly available information. We use ten macroeconomic and financial variables as the predicting variables. At each month, one predicting model for stock return and one for bond return are selected according to predefined criterion. Based on the selected forecasting models, the Sharpe ratio strategy and the Tactical Asset Allocation strategy are used to construct an optimal portfolio. These two active strategies are compared with the passive buy-and-hold stock index strategy, taking into account the transaction costs. The results are really encouraging. In the scenarios of zero and low transaction costs, both active strategies generate substantially higher mean returns with much lower standard deviation than the passive buy-and-hold strategy. Moreover, even with high transaction costs, the active strategies are still superior to passive strategy in terms of Sharpe ratio on the portfolios. This study strongly support that the real-time prediction of UK stock and bond returns is economically significant

High frequency exchange rate prediction with an artificial neural network

This paper examines how market microstructure variables can be used to forecast foreign exchange rates at frequencies of one to several minutes. We use a unique foreign exchange (FX) dataset of global inter-dealer electronic transactions and applied the Artificial Neural Network (ANN) as the predicting model. The immediately preceding bid and ask prices are significant factors in these predictions, which is in keeping with market microstructure theory. These microstructure factors have not been tested in ANN model before. High frequency trading strategies based on ANN model are shown to be profitable even when transaction costs are included