Prostate cancer (PCA) is the second leading cause of cancer-related mortality in men. The glycolytic enzymes hexokinase II (HKII) and the major regulator hypoxia-inducible factor-1α (HIF-1α) are PCA-specific biomarkers. Some studies have shown that HKII and HIF-1α are highly expressive in PCA and are associated with the growth and metastasis of treatment. Whether HKII and HIF-1α regulate the different differentiation of PCA remains largely unknown. Therefore, the study aims to explore the value of HKII and HIF-1α in different grade groups of PCA. Our data indicated that compared with normal prostate tissues, the level of mRNA and protein of HKII and HIF-1α in PCA increased significantly, besides the results showed the high expression of HKII and HIF-1α had a tendency to promote the progression and differentiation of PCA. The study also found that HKII expression was positively correlated with the expression of HIF-1α. HKII and HIF-1α were related to the degree of differentiation PCA, especially in high-grade PCA. Furthermore, the high expression of HKII was significantly associated with Gleason score and histological differentiation in clinicopathological characteristics of patients with PCA. These results were further used to confirm that the expression of HKII and HIF-1α was associated with the progression and differentiation of PCA. These experiments indicated that HKII and HIF-1α might be novel biomarkers of PCA with potential clinical application value, provide a new potential target for PCA treatment, and are expected to be used for individualized treatment in patients with PCA.
Abstract. The apple image segmentation is the key technology of identification and location in the apple-picking machine vision system. On account of huge errors in the process of discriminating fruits by apple-picking robots at present and the long-time processing, the SVM theory in fingerprint image segmentation method is conducted. Combined with the global search ability of particle swarm optimization in solving combinational optimization problems, the SVM partitioning algorithm, which is based on the parameter optimization of particle swarm, is put forward. The results show that this algorithm makes the separation of apple fruits and the image background come true. It also preserves the outline of apples, then polishes the image after segmentation by the close operation in mathematical morphology, which eliminates the pore phenomenon effectively and provides convenience for the further apple-picking and apple-discriminating.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.