Background: Gastrointestinal cancer is one of the most common neoplasms. Cytokeratin 18(CK18) is widely expressed in many different organs and cancers. Emerging data suggested conflicting results about the role of CK18 during carcinogenesis. The aim of this study is to systematically review the prognostic value of circulating CK18 (M65) and caspase-Cleaved CK18 (M30) in digestive cancers. Materials and Methods: We searched major database for manuscripts reporting the effect of pretreatment CK18 on survival of digestive cancer patients. Revman5.3 and R were the software used for analysis. Pooled multivariable-adjusted hazard ratios (HR) for overall survival (OS) were calculated in all patients and many different subgroup analyses by stratifying on tumor type, metastasis stage, and ethnicity. Results: 11 original studies were included for analysis. A low level of M30 and M65 were shown to be a protective factor for all cancer patients (HR 0.49, 95%CI 0.33-0.73, P=0.0003; HR 0.48, 95% CI 0.32-0.70, P =0.0001, respectively). The low M30 remained to be a protective factor for metastasized cancer patients while M65 had no statistically significant correlation with prognosis. Conclusions: Non-invasive total and cleaved CK18 level detection by ELISA could be potentially a useful predictor of prognosis of digestive cancer patients. Further studies are warranted to investigate the molecular mechanisms of CK18.
Although computer image recognition can distinguish very clear images, it is only limited to a certain number of years. Or it can only be clearly distinguishable from some range of graphs, and expanding the range or changing the range will not achieve the state that people want it to achieve. Nowadays, China’s equipment in this field can only conduct activity research in the two-dimensional space, and can only decompose and analyze the two-dimensional pictures. For high-dimensional and complex graphs, they still cannot be processed and the processing requirements are not up to standard. Moreover, the development of this technology is also affected by many human factors. The operation and implementation of this technology mainly rely on the high-energy and powerful processing power of the big data computing system. If we want to ensure the quality of image processing is very good, we must closely combine the recognition image and the related technology of the computer, and do not separate from each other. In this paper, the development of the technology from the status quo, the development of the principle and characteristics of the development of the technology for an in-depth study of the technology, but also the development prospect of the technology is described.
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