Anti-Complement C3 monoclonal antibody, clone 20D8

Realgar (As4S4) has been used in traditional Chinese medicines for treatment of malignancies. The poor solubility of As4S4 hampered its clinical applications. Realgar quantum dots (RQDs) were developed to overcome these problems. Previous studies revealed that the RQDs were effective against endometrial cancer JEC cells and hepatocarcinoma HepG2 cells via inducing apoptosis.Apoptosis and autophagy are important programmed cell death pathways leading to anticancer effects. This study further examined effects of RQDs on autophagy, focusing on the formation of the autophagosome in JEC cells. CCK8 assay was used to examine cell proliferation. Flow cytometry was used to analyze cell cycle. Transmission electron microscopy (TEM) was used to examine the autophagy, cells were transfected with pEGFP-C3-MAP1LC3B plasmid to examine effects of RQDs on autophagosome via confocal microscope. Autophagy-related proteins were examined by Western blot. RQDs exhibited cytotoxicity in JEC cells in a concentration- and time- dependent manner. RQDs induced G2 and S phase arrest in JEC cells. RQDs significantly induced autophagy, with the double-membrane and autophago-some-like structures by TEM. The diffused distribution of pEGFP-C3-MAP1LC3B green fluorescence were become the punctuate pattern fluorescence after treatment with RQDs in cells transfected with pEGFP-C3-MAP1LC3B plasmid RQDs increased the expression of autophagy-regulatory proteins LC3 I/II, Beclin-1, p62 and Atg12 in a concentration-dependent manner, similar to autophagy induced by serum starvation, except for p62, as induction of p62 is a characteristic of arsenic compounds. Taken together, the present study clearly demonstrated that RQDs can induce autophagy in JEC cells as one of mechanisms of anticancer effects, and indicated that RQDs may be developed as an autophagy inducer.

This study aims to control the processing technology of granite aggregate through fractal theory, and to optimize the gradation of concrete to solve the reuse of waste stone derived from the construction and demolition wastes in China. This study applies the waste stone from construction and demolition wastes in concrete and provide a case example for the construction industry to implement the recycle, reuse and reduce principle to affect the management policy of waste stone. The demand for concrete is surging with the continuous expansion of global infrastructure construction. This study presents the process the waste stone produced by excavation along the line to concrete aggregate is a serious problem to be solved. The fractal and gradation theory are employed to investigate the effects of aggregate shape and gradation distribution on the concrete performances, including compressive strength, frost resistance and chloride ion permeability. The larger the fractal dimension of aggregate was, the worse the performance of concrete was. There was always an optimal gradation to optimize the performance of concrete. The 28-day compressive strength of C1 aggregate concrete with larger fractal dimension was 2-3 MPa lower than that of C2 and C3 aggregate concrete. In the freeze-thaw cycle test, the loss of C1 aggregate was 1% more than that of the other two aggregate. 100 times, 200 times and 300 times, the loss of C1 aggregate was reduced by 3-4%, 7-13% and 20% in average. In terms of chloride ion permeability, the impact to chloride ion permeability of graded concrete was greater than that of fractal dimension, and the RCM value of two concrete with worse gradation was about twice as much as that of better gradation concrete. This study conducts the performance analysis and optimize the overall calculation for mix design. The result indicated that larger fractal dimension of aggregate would lead to the worse appeal performance of concrete. When the ratio of 5 mm-10mm aggregate to 10 mm-20mm aggregate is close to 30:70 and the performance is the best. The C50HPC overall calculation method for mix design has achieved better results in engineering practice. (C) 2020 Elsevier Ltd. All rights reserved.