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Mitochondrial DNA (mtDNA) haplogroups are associated with various types of cancer; however, the molecular mechanisms by which mtDNA haplogroups affect primary hepatocellular carcinoma (HCC) are not known. In this study, we carried out a case-control study on 388 HCC patients and 511 geographically matched asymptomatic control subjects in northern China. We found that mtDNA haplogroup N9a and its diagnostic SNP, m.16257C > A, negatively correlated with the incidence of HCC in northern China (odds ratio [OR] 0.290, 95% confidence interval [CI] 0.123–0.685, p = 0.005), particularly in patients with infection of hepatitis B/C virus (HBV/HCV) (for haplogroup N9a: OR 0.213, 95% CI 0.077–0.590, p = 0.003; for m.16257C > A: OR 0.262, 95% CI 0.107–0.643, p = 0.003). However, mtDNA haplogroup N9a is not associated with clinical characteristics of HCC including serum alpha-fetoprotein (AFP) level and tumor size. In addition, cytoplasmic hybrid (cybrid) cells with N9a haplogroup (N9a10a and N9a1) had transcriptome profiles distinct from those with non-N9a (B5, D4, and D5) haplogroups. Gene set enrichment analysis (GSEA) showed that metabolic activity varied significantly between N9a and non-N9a haplogroups. Moreover, cells with haplogroup N9a negatively correlated with cell division and multiple liver cancer pathways compared with non-N9a cells. Although it is still unclear how N9a affects the aforementioned GSEA pathways, our data suggest that mtDNA haplogroup N9a is negatively correlated with the incidence and progression of HCC in northern China.

With the development of 3-D imaging techniques, three dimensional point cloud partition becomes one of the key research fields. In this paper, two data partition algorithms are proposed. Each algorithm includes two parts: data re-organization and data classification. Two methods for data re-organization are proposed: dimension reduction and triangle mesh reconstruction. The algorithm of data classification is based on edge detection of depth data. The edge detection algorithms of gray images are improved for depth data partition. As to the triangulation method, the data partition is realized by region growing. The simulation result shows that the two methods can achieve point cloud data partition of standard template and real scene. The result of standard template shows the total error rates of the two algorithms are both less than 3%.

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