Evidence for Anticancer Effects of Chinese Medicine Monomers on Colorectal Cancer.

Colorectal cancer is one of the most commonly occurring cancers worldwide. Although clinical reports have indicated the anticancer effects of Chinese herbal medicine, the multiple underlying molecular and biochemical mechanisms of action remain to be fully characterized. Chinese medicine (CM) monomers, which are the active components of CM, serve as the material basis of the functional mechanisms of CM. The aim of this review is to summarize the current experimental evidence from in vitro, in vivo, and clinical studies for the effects of CM monomers in colorectal cancer prevention and treatment, providing some useful references for future research.

Psychometric Evaluation of the Fear of COVID-19 Scale Among Chinese Population.

Fear is a negative emotional reaction to or persistent worry over an imminent public health event like COVID-19. The COVID-Fear Scale was developed in many countries, but not in China. The current study aims to examine the psychometric properties of Chinese version of the Fear of COVID-19 Scale. Translation into Chinese and back-translation into English were conducted firstly. Item analysis and exploratory factor analysis were conducted in Sample 1, followed by validity tests in Sample 2. Likely, test-retest reliability was conducted in sample 3. A bifactor structure of Chinese version of FCV-19S with a general fear factor and two orthogonal group factors with fear thoughts and physical response was confirmed. Besides, it has good internal consistency reliability (α = .92), composite reliability (CR = .92), and validity correlation validity. The results of the present study confirmed that the Chinese version of FCV-19S has good psychometric properties in the Chinese communities. Supplementary Information: The online version contains supplementary material available at 10.1007/s11469-020-00441-7.

A Chaotic Neural Network Model for English Machine Translation Based on Big Data Analysis.

In this paper, the chaotic neural network model of big data analysis is used to conduct in-depth analysis and research on the English translation. Firstly, under the guidance of the translation strategy of text type theory, the translation generated by the machine translation system is edited after translation, and then professionals specializing in computer and translation are invited to confirm the translation. After that, the errors in the translations generated by the machine translation system are classified based on the Double Quantum Filter-Muttahida Quami Movement (DQF-MQM) error type classification framework. Due to the characteristics of the source text as an informative academic text, long and difficult sentences, passive voice, and terminology translation are the main causes of machine translation errors. In view of the rigorous logic of the source text and the fixed language steps, this research proposes corresponding post-translation editing strategies for each type of error. It is suggested that translators should maintain the logic of the source text by converting implicit connections into explicit connections, maintain the academic accuracy of the source text by adding subjects and adjusting the word order to deal with the passive voice, and deal with semitechnical terms by appropriately selecting word meanings in postediting. The errors of machine translation in computer science and technology text abstracts are systematically categorized, and the corresponding post-translation editing strategies are proposed to provide reference suggestions for translators in this field, to improve the quality of machine translation in this field.

Emodin suppresses growth and invasion of colorectal cancer cells by inhibiting VEGFR2.

Emodin can effectively inhibit colorectal cancer cells, but the mechanism remains elusive. This study analyzed the changes of VEGFR2 signaling pathways in patients with colorectal cancer and the effects of emodin on HCT116 cells and xenograft tumor model. The expression levels of VEGFR2, PI3K, and p-AKT in colorectal cancer tissue samples were significantly higher than those in adjacent normal ones. Docking simulation confirmed that emodin bound the hydrophobic pocket and partially overlapped with the binding sites of VEGFR2, thus disrupting VEGFR2 dimerization. Western blotting further confirmed that emodin significantly inhibited the expression of VEGFR2, and reduced the expressions of PI3K and p-AKT in HCT116 cells. Furthermore, it suppressed the growth, adhesion and migration of HCT116 cells. In addition, emodin inhibited the tumor growth in xenograft model and the expressions of VEGFR2, PI3K and p-AKT in vivo. In conclusion, emodin suppressed the growth of colorectal cancer cells by inhibiting VEGFR2, as a potential candidate for therapy.

Celastrol inhibits colorectal cancer through TGF-ß1/Smad signaling.

BACKGROUND: There are few clinical challenges associated with the treatment of colorectal cancer (CRC). Studies have shown that TGF-ß plays a crucial role in CRC. Importantly, celastrol, a major components of the root extract of the traditional Chinese herb Tripterygium wilfordii Hook F, has been shown to inhibit the growth, adhesion, and metastasis of human CRC cells through the inhibition of TGF-ß1/Smad signaling. MATERIALS AND METHODS: Real-time PCR and Western blot tests were proceeded to present TGF-ß1, TGF-ß receptor type I (TGFßRI), TGF-ß receptor type II (TGFßRII), Smad2/3, p-Smad2/3, Smad4, and glyceraldehyde-3-phosphate dehydrogenase expression in human colon cancer cell samples. RESULTS: Our results indicated that celastrol can reduce the expression levels of TGF-ß1, TGFßRI, and TGFßRII in HCT116 and SW620 cells. Furthermore, celastrol could also prevent the increase in Smad4 and p-Smad2/3 in HCT116 and SW620 cells. CONCLUSION: Celastrol could inhibit tumor growth through TGF-ß1/Smad signaling and might be a promising therapeutic component against CRC.

Coptisine suppresses tumor growth and progression by down-regulating MFG-E8 in colorectal cancer.

Treating colorectal cancer (CRC) continues to be a clinical challenge. Coptisine, an alkaloid derived from Coptis chinensis Franch. shows toxic effects on CRC cells, but its underlying mechanism remains elusive. MFG-E8 is involved in tumor growth and progression. Herein, we evaluated the effects of coptisine on MFG-E8 in CRC, and explored the mechanism. The expression of MFG-E8 in CRC and adjacent normal colon tissue samples from patients was detected. The effects of coptisine on CRC cells HCT116 in vitro were evaluated by CCK-8, adhesion and transwell assays. A xenograft tumor model was used to assess the effects of coptisine in vivo. The morphology of CRC tissue was observed by HE staining. Cell signaling was tested using western blotting and immunohistochemical assay. The expression of MFG-E8 in human CRC tissue samples significantly increased compared with that of adjacent normal ones. Coptisine significantly reduced the expressions of MFG-E8 in HCT116 cells and tumor-bearing mice. Moreover, coptisine suppressed the growth, adhesion and metastasis of CRC cells. Coptisine also suppressed the expression of MMP-2 and MMP-9 via the PI3K/AKT signaling pathway. Furthermore, it inhibited epithelial-mesenchymal transition in vivo and in vitro. Coptisine inhibited CRC growth and progression by down-regulating MFG-E8, and is a potential candidate for treatment.