MTR4 drives liver tumorigenesis by promoting cancer metabolic switch through alternative splicing.

The metabolic switch from oxidative phosphorylation to glycolysis is required for tumorigenesis in order to provide cancer cells with energy and substrates of biosynthesis. Therefore, it is important to elucidate mechanisms controlling the cancer metabolic switch. MTR4 is a RNA helicase associated with a nuclear exosome that plays key roles in RNA processing and surveillance. We demonstrate that MTR4 is frequently overexpressed in hepatocellular carcinoma (HCC) and is an independent diagnostic marker predicting the poor prognosis of HCC patients. MTR4 drives cancer metabolism by ensuring correct alternative splicing of pre-mRNAs of critical glycolytic genes such as GLUT1 and PKM2. c-Myc binds to the promoter of the MTR4 gene and is important for MTR4 expression in HCC cells, indicating that MTR4 is a mediator of the functions of c-Myc in cancer metabolism. These findings reveal important roles of MTR4 in the cancer metabolic switch and present MTR4 as a promising therapeutic target for treating HCC

Chaperone-assisted translocation of a polymer through a nanopore

Using Langevin dynamics simulations, we investigate the dynamics of chaperone-assisted translocation of a flexible polymer through a nanopore. We find that increasing the binding energy $\epsilon$ between the chaperone and the chain and the chaperone concentration $N_c$ can greatly improve the translocation probability. Particularly, with increasing the chaperone concentration a maximum translocation probability is observed for weak binding. For a fixed chaperone concentration, the histogram of translocation time $\tau$ has a transition from long-tailed distribution to Gaussian distribution with increasing $\epsilon$. $\tau$ rapidly decreases and then almost saturates with increasing binding energy for short chain, however, it has a minimum for longer chains at lower chaperone concentration. We also show that $\tau$ has a minimum as a function of the chaperone concentration. For different $\epsilon$, a nonuniversal dependence of $\tau$ on the chain length $N$ is also observed. These results can be interpreted by characteristic entropic effects for flexible polymers induced by either crowding effect from high chaperone concentration or the intersegmental binding for the high binding energy.Comment: 10 pages, to appear in J. Am. Chem. So

Visualization of small-angle X-ray scattering datasets and processing-structure mapping of isotactic polypropylene films by machine learning

With the rapid development of the synchrotron radiation X-ray characterization techniques, the preprocessing of large small-angle X-ray scattering (SAXS) datasets and the data mining become urgent requirements for researchers. In this work, we apply the variational autoencoder (VAE) and the conditional variational autoencoder (cVAE) to visualize a large SAXS dataset of hard-elastic isotactic polypropylene (iPP) films in 2- and 1-dimensional latent spaces. The low-dimensional representations enable us to capture key features of the dataset rapidly, such as the similarity among SAXS patterns and the structural evolution trends. The preprocessing of the dataset points out the further direction of data analysis so that researchers can focus on the most valued regions in the dataset. Then, we develop a hybrid VAE-multilayer perceptron (MLP) neural network to realize the processing-structure mapping of iPP films. The robustness of the hybrid VAE-MLP network is verified. Finally, SAXS patterns in the temperature-strain space are generated, which allows us to explore the processing parameter space not involved by previous experiments. These capabilities indicate that the developed machine-learning methods are valuable artificial intelligence toolset to assist in the preprocessing of large-scale SAXS datasets and the establishment of comprehensive processing-structure relationship of hard-elastic iPP films

Design and calibration of the accurate torque measurement systems of the precision robot reducer detector

The input and output torque testing is crucial for improving the quality of Industry robot reducers. In this study, the TMMISR and TMMOSR for a vertical-type robot reducer detector were designed. The length of measurement chain between the torque transducer and the tested reducer was shorten. The overall stiffness of this instrument has been improved through structural optimization. The characteristics of the two main parts of the torque-measurement errors were also analyzed. A high precision torque calibrator with a standard torque output is used to handle the torque calibration process. An error compensation method based on a backpropagation neural network was adopted for the error compensation process in this study. After error compensation, torque-measurement precision of 0.1% can be achieved by the reducer detector over the full torque measurement scale, and the instrument can be used for both static and dynamic measurements

Multiscale velocity unified theory to characterize microscale structure of electrodes and transfer mechanism in CO2 capture

Electrodes and transfer processes are the key to thermal electrochemical CO2 capture. The lifetime of electrodes and capture performance are significantly affected by the microscale (micro- and nanocrystalline) structural change and transfer mechanism. Experimental and time-consuming theoretical studies are expensive, and it is difficult to understand microscale structural changes and transfer mechanism due to a lack of relevant unified knowledge. Thus, a time-saving multiscale velocity unified theory was developed by synergizing the molecular motion and matter movement. The theory well predicts the microscale structural change in electrodes and quantifies the chemical reaction and heat and mass transfer under normal and superhigh/superlow operating conditions. A porous electrode and U-shaped multilayer electrode were designed, and the lifetime of electrodes increased by 30%. The U-shaped multilayer electrode self-repairs its microscale structure, and its mass transfer coefficient increased by 15%. The theory simplifies the computational fluid dynamics and molecular dynamics simulation

A plastic-damage approach to the excavation response of a circular opening in weak rock

During opening construction, the accumulated wall displacement and the developing excavation damaged zone are the results of stress redistribution and inelastic behavior induced by both the microcracking damage and the irreversible plastic deformation. The current approach to predict ground response to excavation disturbance is usually based on the Convergence-Confinement Method, which fails to consider the rock damage and the plastic-damage coupled mechanism, resulting in inaccurate estimation of rock deformation, particularly in the case of the weak rock with high deformability. This study establishes a plastic-damage theoretical approach for a circular opening by a kinematic decomposition of strains into an elastic, plastic and damage parts within the framework of finite strain using a hypoelastic–plastic theory, in order to investigate the inelastic behavior-induced excavation response. In this regard, the damage model provides the effective stress to the plasticity model defining the yield criterion, in combination with the strength-stiffness degradation and damage evolution. The numerical implementation is given and two examples are considered for validation. Extensive works are then carried out to clarify some issues, including the capacity of the model to characterize the inelastic behavior, the role of rock damage and confining stress dependence on ground response, and the preliminary critical support pressure for the residual failure zone.This work is funded by the National Natural Science Foundation of China (Grant Nos. 52004053, U1906208 and 52074060), Natural Science Foundation of Liaoning Province (Grant No. 2021-BS-052), and Fundamental Research Funds for the Central Universities (Grant No. N2101028). These supports are gratefully acknowledged.Peer ReviewedPostprint (author's final draft

Determining the performance for an integrated process of COD removal and CO2 capture

Sludge water with high COD and CO emission in industry pollutes the environment. In order to effectively mitigate the COD and CO, this study developed an integrated process of COD removal and CO capture by utilizing CO to intensify the COD removal process. The mass transfer model and gas and liquid two phase flow model were developed and validated by the experiment. The dynamical characteristic, COD removal and CO capture performance were accurately investigated. The effect of the flue gas, Ca(OH) solution and sludge water on the COD removal and CO capture were discussed in detail. Due to the bond effect of Ca-O-C and large contact area, the highest CO capture efficiency reached 93.1% at simultaneous COD removal. The CO intensification effect on the COD removal was analyzed by the density functional theory. It was found that CO made the Ca(OH) remove COD more stably due to CO controlling the free ions. The CO and Ca(OH) regenerated efficiency respectively reached 85.3% and 88.9% by the electrochemical method