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MicroRNAs, small non-coding RNA molecules, have gained a reputation of the most substantial regulators in gene network with the ability to down-regulate their targets. Accumulating evidence shifted insight toward microRNAs regulation as the key element of cancer initiation, development, and aggression. Recent studies have attached the importance of traditional Chinese medicine (TCM) to the treatment of various cancers, and the functional natural compounds have been considered as novel anticancer agents to directly inhibit tumor progression. In more recent decades, a wide range of biologically active components of TCM has gained increasing attention to their applications in the modulation of microRNAs. This review is on the purpose of demonstrating the significance of TCM bioactive ingredients in microRNAs regulation for cancer treatment according to the reports mainly in the recent six years, providing the evidence of efficient Chinese herbal medicine-based therapy and effective pro-diagnosis focusing on microRNAs expression of cancer patients.

German biotech innovator Altona Diagnostics launches BioNexus-certified regional hub in Malaysia: ADT Biotech Sdn Bhd.

FEI launches "Explore the Unseen" image contest in partnership with National Geographic.

BIO applauds Representative Kaptur's Energy Investment Act of 2012.

Cytori to utilize Sistemic's SistemQC™ to strengthen understanding of mechanisms & support design of Next-Generation Cell Therapies.

Bosch packaging technology and Sartorius Stedim Biotech introduce PreVAS.

CellCentric and ZoBio enter into partnership to develop lead compounds against epigenetic drug targets.

Metabolic pathways play a crucial role in understanding the biochemistry of organisms. In metabolic pathways, modules refer to clusters of interconnected reactions or sub-networks representing specific functional units or biological processes within the overall pathway. In pathway modules, compounds are major elements and refer to the various molecules that participate in the biochemical reactions within the pathway modules. These molecules can include substrates, intermediates and final products. Determining the presence relation of compounds and pathway modules is essential for synthesizing new molecules and predicting hidden reactions. To date, several computational methods have been proposed to address this problem. However, all methods only predict the metabolic pathways and their types, not the pathway modules. To address this issue, we proposed a novel deep learning model, DeepRT that integrates message passing neural networks (MPNNs) and transformer encoder. This combination allows DeepRT to effectively extract global and local structure information from the molecular graph. The model is designed to perform two tasks: first, determining the present relation of the compound with the pathway module, and second, predicting the relation of query compound and module classes. The proposed DeepRT model evaluated on a dataset comprising compounds and pathway modules, and it outperforms existing approaches.

The effect of vinyl acetate (VA) content in ethylene vinyl acetate (EVA) copolymer on the mechanical properties of polypropylene was investigated. Three different EVA copolymers with concentrations of 3 wt%, 6 wt%, 9 wt%, 12 wt% and 15 wt%, were blended to polypropylene. The mechanical properties such as yield and tensile strengths, elastic modulus, Izod impact strength, hardness and melt flow index of the blends were investigated. Relationship between type of vinyl acetate and concentrations, mechanical, MFI and morphological properties were explored.

In this chapter, the evolutionary features and compound relationships of tectonic systems are introduced. Five evolutionary features are proposed as follows: phase, inheritance, migration, difference and conversion, showing the complexity of all tectonic systems. The genetic evolution of various blocks is controlled by tectonic systems, while the formation and evolution of tectonic systems are controlled and affected by various blocks. Their interactions have created the current global tectonic pattern and land–sea changes and evolution.

The Arsenic in steel commonly comes from a certain amount of iron ore but it is difficult to remove them in the iron and steelmaking process because its oxidation potential is lower than that of Iron. In this study, a certain amount of rare earth metal, Cerium and a metal with low melting point, Arsenic were closed in the barrel-shaped cylinder machine by H08 steel, heated to 1323K for 50 hours. Interaction among the cerium, arsenic and iron in the barrel-shaped cylinder were studied by X-ray diffraction, optical microscopy, and electronic probe microscopy analysis. The result shows that the ternary compound Ce12Fe57.5As41 can be developed at 1323K when the atomic ratio of Cerium to Arsenic is 1:3. The binary compound CeAs is the main product at 1323K in the Fe-As-Ce system. The eutectic compound Fe2As can be precipitated from ferrite with the temperature decreasing.