Objective To study the complexity of helical tomotherapy plans for different anatomical sites and explore its correlations with dosimetric verification.Methods A total of 71 complexity metrics of the helical tomotherapy plans executed by Accuray?planning system v.5.1.9.2 for nasopharyngeal carcinoma(n=52),breast cancer(n=19),cervical cancer(n=52)and central nervous system cancer(n=37)were analyzed.The correlations between metrics were analyzed,and principal component analysis was used for dimensionality reduction.The global complexity score(normalized plan complexity score,nPCS)was calculated.The top-contributing complexity metrics within the first 10 principal components were extracted,and a correlation analysis with the gamma passing rate was conducted.Results There was no significant correlation between most metrics.The global complexity score was different for different sites,with the highest median nPCS and the most complex plan in the head and neck cancer.The correlation analysis between the global complexity score and gamma passing rate revealed that in the central nervous system plans,CFNS90 and EPSTV1_0 had strong correlations with gamma passing rate for 3%/2 mm criterion,and a significant correlation was found between CFNS90 and gamma passing rate for 3%/3 mm criterion.Conclusion Complexity scores can quantize the complexity of helical tomotherapy plans for different sites,and certain metrics are correlated with gamma passing rate.

Objective To study the complexity of helical tomotherapy plans for different anatomical sites and explore its correlations with dosimetric verification.Methods A total of 71 complexity metrics of the helical tomotherapy plans executed by Accuray?planning system v.5.1.9.2 for nasopharyngeal carcinoma(n=52),breast cancer(n=19),cervical cancer(n=52)and central nervous system cancer(n=37)were analyzed.The correlations between metrics were analyzed,and principal component analysis was used for dimensionality reduction.The global complexity score(normalized plan complexity score,nPCS)was calculated.The top-contributing complexity metrics within the first 10 principal components were extracted,and a correlation analysis with the gamma passing rate was conducted.Results There was no significant correlation between most metrics.The global complexity score was different for different sites,with the highest median nPCS and the most complex plan in the head and neck cancer.The correlation analysis between the global complexity score and gamma passing rate revealed that in the central nervous system plans,CFNS90 and EPSTV1_0 had strong correlations with gamma passing rate for 3%/2 mm criterion,and a significant correlation was found between CFNS90 and gamma passing rate for 3%/3 mm criterion.Conclusion Complexity scores can quantize the complexity of helical tomotherapy plans for different sites,and certain metrics are correlated with gamma passing rate.

AIM:This study aims to investigate the effects and mechanisms of silent information regulator 6(SIRT6)on carbon tetrachloride(CCl4)-induced liver fibrosis in mice,as well as the expression changes in the down-stream pathways of hepatic stellate cells after SIRT6 silencing.METHODS:Thirty male C57BL/6J mice were randomly divided into a normal control group(n=6)and a model group(modeling at 2,4,8,12 weeks,n=24).A liver fibrosis model in mice was prepared by intraperitoneal injection of CCl4 twice a week for 12 weeks.Serum alanine aminotransfer-ase(ALT)and aspartate aminotransferase(AST)levels were measured to assess liver injury.Hematoxylin-eosin(HE)and Masson staining were used to observe the pathological changes in mouse liver tissues.Immunohistochemical staining was conducted to detect the expression of α-smooth muscle actin(α-SMA)in the liver,Western blot analysis was used to measure the expression of liver α-SMA,SIRT6,acetyl histone H3 at Lys9(H3K9ac),acetyl histone H3 at Lys56(H3K56ac),interleukin-1β(IL-1β),and IL-18 proteins.Hepatic stellate cells-T6(HSC-T6)underwent SIRT6 gene si-lencing,divided into NC siRNA group and SIRT6 siRNA group,with Western blot performed to detect the expression of SIRT6,H3K9ac,and H3K56ac proteins.RESULTS:Compared with the normal control group,the serum ALT and AST levels in the model group were significantly increased(P<0.05);HE and Masson staining results showed that the patho-logical changes in the liver of the model group worsened over time,with an increase in collagen fiber deposition.Both im-munohistochemistry and Western blot showed that the expression of liver α-SMA significantly increased at 8 and 12 weeks in the model group(P<0.05).Western blot results showed that the expression of SIRT6 protein in the liver of all model group mice was lower than that in the normal control group(P<0.05),and decreased gradually with the progression of liv-er fibrosis;also,the expression levels of H3K9ac,H3K56ac,IL-1β,and IL-18 in the liver of the model group mice were significantly elevated at 8 and 12 weeks(P<0.05);after SIRT6 silencing,compared with the NC siRNA group,the levels of H3K9ac and H3K56ac in the SIRT6 siRNA group significantly increased(P<0.05).CONCLUSION:The deficiency of SIRT6,by abnormally increasing H3K9ac and H3K56ac,raises the expression of IL-1β and IL-18,intensifying the in-flammatory response and promoting the progression of liver fibrosis,indicating that the aberrant expression of SIRT6 is in-volved in the development of liver fibrosis.

Objective:To investigate whether SKA1 is a key molecule regulating malignant proliferation of liver cancer, and further explore its mechanism to provide molecular theoretical basis for subsequent targeted therapy.Methods:The data of liver cancer from TCGA database were analyzed by bioinformatics technology. The expression of SKA1 in liver cancer was analyzed. At the same time, we also analyzed the relationship between the expression of SKA1 and the prognosis of patients with liver cancer. The hepatoma cell line overexpressing SKA1 was constructed by liposome-mediated cell transfection technique, and the effect of SKA1 on the proliferation of hepatoma cells was further tested by CCK-8 and plate cloning assay. At the same time, we found that E2F1 is also highly expressed in liver cancer, using bioinformatics technology to analyze the correlation between SKA1 and E2F1 expression, further detecting the binding site of E2F1 in the SKA1 promoter region, and using dual luciferase technology to detect E2F1 against SKA1. Transcriptional activation.Results:KA1 was highly expressed in liver cancer tissues, and the overall survival rate of liver cancer patients with high SKA1 expression was 49.8%, lower than that of patients with low SKA1 expression, showing a negative correlation. E2F1 is also highly expressed in liver cancer tissues, and the survival time of patients with liver cancer with high E2F1 expression is significantly lower than that in the low expression group, which was negatively correlated with poor prognosis. SKA1 overexpression could increase the proliferation ability of liver cancer cells by nearly 50%. SKA1 is regulated by the E2F1 transcription factor, and the E2F1 transcription factor is combined with the SKA1 promoter to transcriptionally activate the expression of SKA1 in liver cancer cells.Conclusion:E2F1 transcriptional activation of SKA1 promotes proliferation of hepatoma cells, leading to poor prognosis in patients with liver cancer