UBE2C promotes the proliferation of acute myeloid leukemia cells through PI3K/AKT activation.

This study aims to investigate the role and mechanism of tubiquitin-conjugating enzyme E2 C (UBE2C) in acute myeloid leukemia (AML). Initially, UBE2C expression in leukemia was analyzed using the Cancer Genome Atlas database. Further, we silenced UBE2C expression using small-hairpin RNA (sh-RNA). UBE2C expression was detected via the quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR) and Western blot analysis. Apoptotic events and reactive oxygen species (ROS) levels were detected by flow cytometry. A xenograft model of leukemia cells were established, and the protein levels of UBE2C, KI-67, and cleaved-caspase 3 were detected by immunohistochemistry. We reported an overexpression of UBE2C in leukemia patients and cell lines (HL60, THP-1, U937, and KG-1 cells). Moreover, a high expression level of UBE2C was correlated with a dismal prognosis in AML patients. UBE2C knockdown inhibited the viability and promoted apoptosis in AML cells by regulating the phosphatidylinositol-3-kinase (PI3K)/protein kinase B (AKT) signaling pathway. Furthermore, UBE2C knockdown increased cellular Fe2+ and ROS levels, and enhanced erastin-induced ferroptosis in a proteasome-dependent manner. UBE2C knockdown also suppressed the tumor formation of AML cells in the mouse model. In summary, our findings suggest that UBE2C overexpression promotes the proliferation and inhibits ferroptosis in AML cells by activating the PI3K/AKT pathway.

Spatial and temporal analysis of influential factors on motor vehicle carbon monoxide emissions in China considering emissions trading scheme.

The number of cars is increasing every year and the environmental aspects of transport are becoming a hot topic. The spatial and temporal patterns of motor vehicle carbon monoxide (CO) emissions are still unclear due to the unbalanced economic development and heterogeneous geographic conditions of China. With the objective of realizing a reduction in motor vehicle CO emissions, his study explores the transport carbon emission reduction pathways of China from motor vehicle CO emission. Firstly, the entropy method is adopted to comprehensively evaluate the CO emissions from motor vehicles in each province; secondly, the development of a Geographically and Temporally Weighted Regression (GTWR) model facilitates the examination of the spatiotemporal dynamics pertaining to the influencing factors of motor vehicle CO emissions within each province.; finally, the characteristics of motor vehicle CO emissions in ETS pilot areas and non-ETS pilot areas are compared. The results show that: (1) After the completion of the six ETS pilot areas in 2011, the CO emission from motor vehicles is reduced by 18% compared with 2010.(2)The entropy method shows that the largest CO emissions from motor vehicles are from Beijing, Shanghai, Guangdong and other provinces with high economic levels.(3) The results of the GTWR model show that the positive effects of economic level, population size, road mileage intensity and motor vehicle intensity on motor vehicle CO emissions are decreasing year by year. The negative effect of metro line intensity on CO emission decreases year by year. This study can help decision makers to identify the high emission areas, understand the influencing factors, and formulate emission reduction measures to achieve the purpose of carbon emission reduction in transport.