Small RNA sequencing reveals dynamic microRNA expression of important nutrient metabolism during development of Camellia oleifera fruit.

To obtain insight into the function of miRNAs in the synthesis and storage of important nutrients during the development of Camellia oleifera fruit, Illumina sequencing of flower and fruit small-RNA was conducted. The results revealed that 797 miRNAs were significantly differentially expressed between flower and fruit samples of Camellia oleifera. Through integrated GO and KEGG function annotations, it was determined that the miRNA target genes were mainly involved in metabolic pathways, plant hormone signal transduction, fruit development, mitosis and regulation of biosynthetic processes. Carbohydrate accumulation genes were differentially regulated by miR156, miR390 and miR395 in the fruit growth and development process. MiR477 is the key miRNA functioning in regulation of genes and involved in fatty acid synthesis. Additionally, miR156 also has the function of regulating glycolysis and nutrient transformation genes.

Dacomitinib antagonizes multidrug resistance (MDR) in cancer cells by inhibiting the efflux activity of ABCB1 and ABCG2 transporters.

The development of multidrug resistance (MDR) to chemotherapy remains a major challenge in the treatment of cancer. Numerous mechanisms have been recognized that cause MDR, but one of the most important mechanisms is overexpression of adenosine triphosphate (ATP)-binding cassette (ABC) transporters, through which the efflux of various anticancer drugs against their concentration gradients is powered by ATP. In recent years, small molecular tyrosine kinase inhibitors (TKIs) have been developed for treatment in various human cancers overexpressing epidermal growth factor receptor (EGFR). At the same time, some TKIs have been shown to be capable of inhibiting ABC transporter-mediated MDR. Dacomitinib (PF-00299804) is a second generation, irreversible TKI, which has shown positive anticancer activities in some preclinical and clinical trials. As many TKIs are substrates or inhibitors of ABC transporters, this study investigates whether dacomitinib could interact with ABC subfamily members that mediate MDR, including ABCB1 (P-gp), ABCG2 (BCRP) and ABCC1 (MRP1). The results showed that dacomitinib at 1.0 µM significantly reversed drug resistance mediated by ABCB1 and ABCG2, but not ABCC1, doing so by antagonizing the drug efflux function in ABCB1- and ABCG2-overexpressing cell lines. The reversal effect on ABCB1-overexpressing cells is more potent than that on ABCG2-overexpressing cells. In addition, dacomitinib at reversal concentration affected neither the protein expression level nor the localization of ABCB1 and ABCG2. Therefore, the mechanisms of this modulating effect are likely to be the following: first, as an inhibitor of ABCB1 or ABCG2 transporters, dacomitinib binds to drug-substrate site in transmembrane domains (TMD) stably in a noncompetitive manner; or second, dacomitinib inhibits ATPase activity and maintains the stability of TMD conformation in a concentration-dependent manner thereby inhibiting the drug efflux function of ABCB1 or ABCG2 transporter. This study provides a useful combinational therapeutic strategy with dacomitinib and substrates of ABCB1 and/or ABCG2 transporters in ABCB1- or ABCG2-overexpressing cancers.

[PM10 Concentration Forecasting Model Based on Wavelet-SVM].

PM10 is the main air pollutant in Taiyuan, as the city is a heavy industrial center with coal as its main energy source. Therefore, research on the prediction of this pollutant's variation and concentration is of great theoretical significance for air pollution prevention and emergency solutions. The source of PM10 is very complex, as it is affected by industrial emissions, vehicle exhaust, fugitive dust, and many other factors. The emission sources of PM10 are difficult to determine accurately. The goal of our research was to give accurate forecasting results efficiently when only time-series PM10 concentrations, and no other exogenous information, is available. A support vector machine (SVM) enjoys good generalization performance in the PM10 concentration forecasting area. Traditionally, an SVM chooses historical data as the input features in the process of dealing with the time-series data of air pollutant concentrations. However, data with simple structure and incomplete information have become the fetter of generalization ability improvement. In this study, the data for simulation experiments was the PM10 concentration dataset collected from four monitoring stations in Taiyuan. The PM10 concentration time-series one-dimension data was decomposed into high dimension, constructed by low frequency and high frequency series using a wavelet transform. The wavelet-SVM forecasting model can be established by introducing the high-dimension data as the input features. The experiment results indicate that, contrasted with the traditional SVM, the wavelet-SVM model boasts higher accuracy for PM10 concentration prediction. In particular, it captures the concentration mutational points more accurately and provides information support that is more effective for atmospheric pollution warning. In addition, with the wavelet-SVM model, prediction accuracy for the concentration variations was significantly improved and laws that were more inherent in the PM10 concentration time series were revealed.

[Hydrologic processes of the different landscape zones in Fenhe River headwater catchment].

There are few studies on the hydrologic processes of the landscape zone scales at present. Since the water environment is worsening, there is sharp contradiction between supply and demand of water resources in Shanxi province. The principle of the hydrologic processes of the landscape zones in Fenhe River headwater catchment was revealed by means of isotope tracing, hydrology geological exploration and water chemical signal study. The results showed that the subalpine meadow zone and the medium high mountain forest zone were main runoff formation regions in Fenhe River headwater catchment, while the sparse forest shrub zone and the mountain grassland zone lagged the temporal and spatial collection of the precipitation. Fenhe River water was mainly recharged by precipitation, groundwater, melt water of snow and frozen soil. This study suggested that the whole catchment precipitation hardly directly generated surface runoff, but was mostly transformed into groundwater or interflow, and finally concentrated into river channel, completed the "recharge-runoff-discharge" hydrologic processes. This study can provide scientific basis and reference for the containment of water environment deterioration, and is expected to deliver the comprehensive restoration of clear-water reflowing and the ecological environment in Shanxi province.