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Wuxiao, Zhi-Jun,Zhou, Hai-Yan,Wang, Ke-Feng,Chen, Xiao-Qin,Hao, Xin-Bao,Lu, Yan-Da,Xia, Zhong-Jun Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.2
Background: Stage III colon cancer patients demonstrate diverse clinical outcomes. The aim of this study was to develop a prognostic model in order to better predict their survival. Materials and Methods: From 2004 to 2010, 548 patients were retrospectively analyzed, among whom 328 were defined as the study group and the remaining 220 served as a validation group. Clinico-pathologic features, including age, gender, histological grade, T stage, number of positive lymph nodes, number of harvest lymph nodes, pretreatment carcinoembryonic antigen (CEA) levels and pretreatment neutrophil lymphocyte ratio (NLR), were collected. Kaplan-Meier survival curves were used to detect prognostic factors and multivariate analysis was applied to identify independent examples on which to develop a prognostic model. Finally, the model was further validated with the validation group. Results: Histological grade (p=0.002), T stage (p=0.011), number of positive lymph nodes (p=0.003), number of harvested lymph nodes (p=0.020), CEA (p=0.005), and NLR (p<0.001) were found as prognostic factors while histological grade [RR(relative risk):0.632, 95%CI (Confidence interval) 0.405~0.985, p=0.043], CEA (RR:0.644, 95%CI:0.431~0.964, p=0.033) and NLR (RR:0.384, 95%CI:0.255~0.580, p<0.001) levels were independent. The prognostic model based on these three factors was able to classify patients into high risk, intermediate and low risk groups (p<0.001), both in study and validation groups. Conclusions: Histological grade, pretreatment CEA and NLR levels are independent prognostic factors in stage III colon cancer patients. A prognostic model based on these factors merits attention in future clinical practice.
From 3D to 4D printing: approaches and typical applications
Ye Zhou,Wei Min Huang,Shu Feng Kang,Xue Lian Wu,Hai Bao Lu,Jun Fu,Haipo Cui 대한기계학회 2015 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.29 No.10
With the additional dimension, 4D printing is emerging as a novel technique to enable configuration switching in 3D printed items. Inthis paper, four major approaches, namely self-assembly of elements, deformation mismatch, bi-stability, and the Shape memory effect(SME), are identified as the generic approaches to achieve 4D printing. The main features of these approaches are briefly discussed. Utilizingthese approaches either individually or in a combined manner, the potential of 4D printing to reshape product design is demonstratedby a few example applications.