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Engineering topics

Wang, Yangang

Publications and source records attributed to Wang, Yangang.

Hepatic conditional knockout of ATF6 exacerbates liver metabolic damage by repressing autophage through MTOR pathway

Highlights: • Conditional knockout of ATF6 exacerbates liver metabolic damage. • Conditional knockout of ATF6 represses autophage. • Conditional knockout of ATF6 activates MTOR pathway. The liver is a central metabolic organ. Activating transcription factor 6 (ATF6) acts as an ER stress responsive gene and is reported to attenuate hepatic steatosis. Over expressing a dominant-negative form of ATF6 exacerbates glucose intolerance and insulin resistance. In the present study, we used the conditional knockout technique to specifically knockout ATF6 in the mouse liver. We used qPCR to detect the mRNA levels of related genes. Western blot analysis was used to evaluate protein levels. Flow cytometry assay showed the apoptosis status. Glucose tolerance tests and insulin tolerance tests were used to determine glucose and insulin sensitivity. The results showed that liver specific knockout of ATF6 exacerbated HFD-induced hepatic steatosis and glucose tolerance. Abolished ATF6 exacerbated gluconeogenic metabolism by MTOR mediated down regulation of autophage. In conclusion, these findings suggest that therapeutic strategies by supplementing ATF6 may be beneficial for the treatment of glucose intolerance as well as insulin resistance in the high fat induced liver metabolic damage condition.

60 APPLIED LIFE SCIENCES↗

Interface Structure Prediction from First-Principles

Information about the atomic structures at solid–solid interfaces is crucial for understanding and predicting the performance of materials. Due to the complexity of the interfaces, it is very challenging to resolve their atomic structures using either experimental techniques or computer simulations. In this paper, we present an efficient first-principles computational method for interface structure prediction based on an adaptive genetic algorithm. This approach significantly reduces the computational cost, while retaining the accuracy of first-principles prediction. The method is applied to the investigation of both stoichiometric and nonstoichiometric SrTiO3 Σ3(112)[1¯10] grain boundaries with unit cell containing up to 200 atoms. Several novel low-energy structures are discovered, which provide fresh insights into the structure and stability of the grain boundaries.

36 MATERIALS SCIENCE↗