Hepatocellular carcinoma (HCC) is highly malignant; nearly half of the new cases and deaths are in China. The poor prognosis of HCC is mainly due to late diagnosis; many new biomarkers have been developed for HCC diagnosis. However, few markers are quickly translated into clinical practice; early and differential diagnosis of HCC from cirrhosis and/or hepatitis is still a clinical challenge. Metabolomics and biochemical methods were used to reveal specific serum biomarkers of HCC. Most of the elevated metabolites in HCC and HBV patients were overlapped compared with controls. Urea was the specifically elevated serum biomarker of HCC patients. Moreover, urea combined with AFP and CEA can improve the sensitivity of HCC diagnosis. The plasma ammonia of HCC patients was significantly higher than healthy controls. Co-culture cell model revealed normal liver cells cooperated with cancer cells to metabolize ammonia into urea. The urea metabolism in cancer cells marginally depended on the expression of CPS1. However, the expression of CPS1 did not change with ammonium chloride, which might regulate the urea cycle through enzyme activity. The urea cycle could detoxify high concentrations of ammonia to promote cancer cell proliferation. Therefore, urea was a by-product of ammonia metabolism and could be a potential serum biomarker for HCC. The combined application of metabolomics and biochemical methods can discover new biomarkers for the early diagnosis of HCC and be quickly applied to clinical diagnosis.
The effect of the substitution of manganese by magnesium on the activity and physicochemical properties of
a LaMn1
-
x
Mg
x
Al11O19 hexaaluminate catalyst was investigated. The samples were prepared using a
coprecipitation method and characterized by X-ray diffractometry (XRD), hydrogen temperature-programmed
reduction (TPR), oxygen temperature-programmed desorption (TPD), and nitrogen adsorption. The results
show that the Mg-substitution enhances the catalytic activity. A sample with a composition of LaMn0.7Mg0.3Al11O19 has a very good activity and T
10% = 704 K. XRD analysis suggests that the partial substitution of
manganese by magnesium effectively suppresses the crystal growth along the [001] direction, which leads to
an improved surface area. Although the increase in activity is partially attributable to the high surface area,
TPD and TPR results confirm that the substitution also affects the oxygen adsorption property and the oxidation
state of Mn ions in the hexaaluminate lattice. The reducibility, the amount of Mn3+ species, and the lattice
oxygen mobility also are improved.
In order to improve the teaching effect of American science fiction literature, based on artificial intelligence virtual reality technology, this paper constructs an auxiliary teaching system of intelligent American science fiction literature. Moreover, this paper analyzes the time complexity and space complexity of constructing point cloud spatial topological relations and finding the nearest k neighboring points. Simultaneously, this paper uses CUDA to find k nearest neighbors on the GPU, analyzes the point cloud denoising technology, uses the KD-tree to construct the point cloud topology in the DBSCAN-based denoising method, searches for the k nearest neighbors to complete the mark of the core point and the boundary point. In addition, this paper combines artificial intelligence virtual technology and intelligent algorithms to construct the framework of the auxiliary teaching system of American science fiction literature, and analyze its functional modules. Finally, this paper designs experiments to verify the performance of the model. The research results show that the system constructed in this paper can meet the needs of auxiliary teaching of American science fiction literature.
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