Background: Lower mean platelet volume(MPV) is an indicator of platelet activity in the setting of tumor development. This study was to assess the relationship between preoperative MPV and survival outcomes of patient...Background: Lower mean platelet volume(MPV) is an indicator of platelet activity in the setting of tumor development. This study was to assess the relationship between preoperative MPV and survival outcomes of patients with hepatocellular carcinoma(HCC) following liver transplantation(LT). Methods: The demographic and clinical characteristics of 304 HCC patients following LT were retrieved from an LT database. All the patients were divided into the normal and lower MPV groups according to the median MPV. The factors were first analyzed using a Kaplan–Meier survival analysis, then the factors with P < 0.10 were selected for multivariate Cox regression analysis and were used to define the independent risk factors for poor prognosis. Results: The 1-, 3-, and 5-year tumor free survival was 95.34%, 74.67% and 69.29% in the normal MPV group, respectively, and 95.40%, 59.97% and 42.94% in the lower MPV group, respectively( P < 0.01). No significant difference was observed in post-LT complications between the normal and lower MPV groups. Portal vein tumor thrombosis(PVTT)[hazard ratio(HR = 2.24;95% confidence interval: 1.46–3.43;P < 0.01) and lower MPV(HR = 1.58;95% confidence interval: 1.05–2.36;P = 0.03) were identified as independent prognostic risk factors for recipient survival. Conclusion: Preoperative lower MPV is a risk indicator of HCC patients survival outcomes after LT.展开更多
OBJECTIVE: To investigate the alloimmunogenicity of liver specific antigen and its effects on allolymphocytes. METHODS: Liver specific antigen isolated from inbred F344 rats was used as immunogen to immunize inbred Le...OBJECTIVE: To investigate the alloimmunogenicity of liver specific antigen and its effects on allolymphocytes. METHODS: Liver specific antigen isolated from inbred F344 rats was used as immunogen to immunize inbred Lew rats through different immunization pathways such as low-dose long-term hind footpad, high-dose portal vein and thymus immunization. Western blotting, DNA fragments gel electrophoresis, mixed lymphocyte culture (MLC) and mixed lymphocyte hepatocyte culture (MLHC) were employed to analyze the immune state after immunization. RESULTS: At the time point of sampling, different degree of specific low immunoresponses appeared in all immunized groups as well as cyclophosphamide (CY) treated group. Compared with group I, other groups expressed caspase-3 significantly as detected by using Western blotting. DNA fragment gel electrophoresis of splenocytes showed lymphocyte apoptosis. Compared with the group I, MLC of the experimental groups showed no significant changes except that of the group V, whereas MLHC decreased markedly (P<0.05). CONCLUSIONS: Liver specific antigen not only has alloimmunogenicity to induce alloimmunoreaction but induce antigen specific low immunoresponses and antigen specific lymphocyte apoptosis by high-dose or low-dose long-term immunization. It may be an important transplantation antigen that may lead to a novel way to liver transplantation immunotolerance.展开更多
The cross-section profile is a key signal for evaluating hot-rolled strip quality,and ignoring its defects can easily lead to a final failure.The characteristics of complex curve,significant irregular fluctuation and ...The cross-section profile is a key signal for evaluating hot-rolled strip quality,and ignoring its defects can easily lead to a final failure.The characteristics of complex curve,significant irregular fluctuation and imperfect sample data make it a challenge of recognizing cross-section defects,and current industrial judgment methods rely excessively on human decision making.A novel stacked denoising autoencoders(SDAE)model optimized with support vector machine(SVM)theory was proposed for the recognition of cross-section defects.Firstly,interpolation filtering and principal component analysis were employed to linearly reduce the data dimensionality of the profile curve.Secondly,the deep learning algorithm SDAE was used layer by layer for greedy unsupervised feature learning,and its final layer of back-propagation neural network was replaced by SVM for supervised learning of the final features,and the final model SDAE_SVM was obtained by further optimizing the entire network parameters via error back-propagation.Finally,the curve mirroring and combination stitching methods were used as data augmentation for the training set,which dealt with the problem of sample imbalance in the original data set,and the accuracy of cross-section defect prediction was further improved.The approach was applied in a 1780-mm hot rolling line of a steel mill to achieve the automatic diagnosis and classification of defects in cross-section profile of hot-rolled strip,which helps to reduce flatness quality concerns in downstream processes.展开更多
基金supported by grants from the Natural Science Foundation of Zhejiang Province(Y17H160118,LY18H030002 and LQ15H030003)the Fundamental Research Funds for the Cen-tral University(2018FZA7002)
文摘Background: Lower mean platelet volume(MPV) is an indicator of platelet activity in the setting of tumor development. This study was to assess the relationship between preoperative MPV and survival outcomes of patients with hepatocellular carcinoma(HCC) following liver transplantation(LT). Methods: The demographic and clinical characteristics of 304 HCC patients following LT were retrieved from an LT database. All the patients were divided into the normal and lower MPV groups according to the median MPV. The factors were first analyzed using a Kaplan–Meier survival analysis, then the factors with P < 0.10 were selected for multivariate Cox regression analysis and were used to define the independent risk factors for poor prognosis. Results: The 1-, 3-, and 5-year tumor free survival was 95.34%, 74.67% and 69.29% in the normal MPV group, respectively, and 95.40%, 59.97% and 42.94% in the lower MPV group, respectively( P < 0.01). No significant difference was observed in post-LT complications between the normal and lower MPV groups. Portal vein tumor thrombosis(PVTT)[hazard ratio(HR = 2.24;95% confidence interval: 1.46–3.43;P < 0.01) and lower MPV(HR = 1.58;95% confidence interval: 1.05–2.36;P = 0.03) were identified as independent prognostic risk factors for recipient survival. Conclusion: Preoperative lower MPV is a risk indicator of HCC patients survival outcomes after LT.
文摘OBJECTIVE: To investigate the alloimmunogenicity of liver specific antigen and its effects on allolymphocytes. METHODS: Liver specific antigen isolated from inbred F344 rats was used as immunogen to immunize inbred Lew rats through different immunization pathways such as low-dose long-term hind footpad, high-dose portal vein and thymus immunization. Western blotting, DNA fragments gel electrophoresis, mixed lymphocyte culture (MLC) and mixed lymphocyte hepatocyte culture (MLHC) were employed to analyze the immune state after immunization. RESULTS: At the time point of sampling, different degree of specific low immunoresponses appeared in all immunized groups as well as cyclophosphamide (CY) treated group. Compared with group I, other groups expressed caspase-3 significantly as detected by using Western blotting. DNA fragment gel electrophoresis of splenocytes showed lymphocyte apoptosis. Compared with the group I, MLC of the experimental groups showed no significant changes except that of the group V, whereas MLHC decreased markedly (P<0.05). CONCLUSIONS: Liver specific antigen not only has alloimmunogenicity to induce alloimmunoreaction but induce antigen specific low immunoresponses and antigen specific lymphocyte apoptosis by high-dose or low-dose long-term immunization. It may be an important transplantation antigen that may lead to a novel way to liver transplantation immunotolerance.
基金supported by the National Natural Science Foundation of China(No.52004029)the Joint Doctoral Program of China Scholarship Council(CSC)(202006460073)Liuzhou Science and Technology Plan Project,China(2021AAD0102).
文摘The cross-section profile is a key signal for evaluating hot-rolled strip quality,and ignoring its defects can easily lead to a final failure.The characteristics of complex curve,significant irregular fluctuation and imperfect sample data make it a challenge of recognizing cross-section defects,and current industrial judgment methods rely excessively on human decision making.A novel stacked denoising autoencoders(SDAE)model optimized with support vector machine(SVM)theory was proposed for the recognition of cross-section defects.Firstly,interpolation filtering and principal component analysis were employed to linearly reduce the data dimensionality of the profile curve.Secondly,the deep learning algorithm SDAE was used layer by layer for greedy unsupervised feature learning,and its final layer of back-propagation neural network was replaced by SVM for supervised learning of the final features,and the final model SDAE_SVM was obtained by further optimizing the entire network parameters via error back-propagation.Finally,the curve mirroring and combination stitching methods were used as data augmentation for the training set,which dealt with the problem of sample imbalance in the original data set,and the accuracy of cross-section defect prediction was further improved.The approach was applied in a 1780-mm hot rolling line of a steel mill to achieve the automatic diagnosis and classification of defects in cross-section profile of hot-rolled strip,which helps to reduce flatness quality concerns in downstream processes.
基金Project supported by the China Postdoctoral Science Foundation(No.2017M610374)the Zhejiang Health Technology Project(No.2019RC153)+1 种基金the Zhejiang Provincial Natural Science Foundation of China(No.Y17H160118)the National Natural Science Foundation of China(No.91542205)