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Objective:To investigate the differences between patients with small cell carcinoma of the cervix and other type of cervical cancer on clinicopathological characteristics,treatment,prognosis through the retrospective analysis,also study the prognostic factors in patients with SCCC.Methods:The patients with SCCC(63 cases,research group) and patients with Non-SCCC(60 cases,control group) such as squamous cell carcinoma and adenocarcinoma of cervix were chosen during May 2003 and June 2015 in department of obstetrics and gynecology,west China second university hospital.The clinical pathological and survival data were collected,sort out,checked and analyzed.Chi-square test or Fisher's exact probability method was used to compare the differences of clinical features between the two groups.The 5-year disease-free survival(DFS) rate and 5-year overall survival(OS) rate were generated using the Kaplan-Meier method.Univariate and multivariate analysis were applied to research the prognostic factors.Results:①The median age of the patients in research group was 40 years old,younger than control group whose median age was 44 years old (P =0.001).The rate of lymph node metastasis,parametrial infiltration,vascular involvement and positive surgical margins in research group were significantly higher than those of control group (P ＜ 0.05).There were no significantly differences between two groups in clinical symptoms,FIGO stage,therapeutic schedule.②In the survival analysis,the research group estimated 5-year overall survival (OS) rate (29.2％) and estimated 5-year disease-free survival rate (DFS)(26.6％) was significantly lower than those of the control group(82.6％,and 76.7％,respectively) P ＜ 0.05.③In the COX multivariate regression analysis,the results showed that the lymph node metastasis was the independent factor influencing overall survival rate and disease-free survival rate(HR =4.784、3.067,P ＜ 0.05).In addition,the tumor size was the independent factor influencing overall survival rate (HR =3.610,P ＜ 0.05),and advanced FIGO staging was the independent factor influencing disease-free survival rate (HR =2.793,P ＜ 0.05).Conclusions:The patients with SCCC were younger than other cervical cancer,and the clinical symptoms,cervical appearance,treatment between the two types are almost the same.However,The rate of lymph node metastasis,parametrial infiltration,vascular involvement and positive surgical margins in patients with SCCC were significantly higher than other cervical cancer,and the prognosis of the patients with SCCC was very poor.The main prognostic factors were lymph node metastasis,advanced FIGO stage and tumor size.
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Classical dictionary learning methods for video coding suffer from high computational complexity and interfered coding efficiency by disregarding its underlying distribution. This paper proposes a spatio-temporal online dictionary learning (STOL) algorithm to speed up the convergence rate of dictionary learning with a guarantee of approximation error. The proposed algorithm incorporates stochastic gradient descents to form a dictionary of pairs of 3D low-frequency and high-frequency spatio-temporal volumes. In each iteration of the learning process, it randomly selects one sample volume and updates the atoms of dictionary by minimizing the expected cost, rather than optimizes empirical cost over the complete training data, such as batch learning methods, e.g., K-SVD. Since the selected volumes are supposed to be independent identically distributed samples from the underlying distribution, decomposition coefficients attained from the trained dictionary are desirable for sparse representation. Theoretically, it is proved that the proposed STOL could achieve better approximation for sparse representation than K-SVD and maintain both structured sparsity and hierarchical sparsity. It is shown to outperform batch gradient descent methods (K-SVD) in the sense of convergence speed and computational complexity, and its upper bound for prediction error is asymptotically equal to the training error. With lower computational complexity, extensive experiments validate that the STOL-based coding scheme achieves performance improvements than H.264/AVC or High Efficiency Video Coding as well as existing super-resolution-based methods in rate-distortion performance and visual quality.
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BACKGROUND: Rat Biot2 is a novel gene first reported and named by our laboratory. We wanted to study the expression profile and reveal the function of its human homologous gene (human Biot2, hBiot2) on carcinogenesis in endometrial cancer. METHODS: Using RT-PCR, we tested hBiot2 expression profile in normal human tissues from infants and adults. Using real-time RT-PCR, we tested different expression quantities of hBiot2 between an endometrial cancer group and a normal endometrium group, between different histological grading groups in endometrial cancer, and between different stage groups during the menstrual cycle. RNA-RNA ISH tested the expression location of hBiot2 in normal and cancer tissues. RESULTS: Three kinds of novel shearings of hBiot2 in different normal tissues were obtained. Normal organs expressing hBiot2 in infants, did not express hBiot2 in adults. hBiot2 expression was higher in endometrial cancer tissue compared to normal endometrium tissue. hBiot2 expression was higher in the Grade 2-3 group with endometrial cancer compared to the Grade 1 group, and it was higher in the proliferative phase than in the secretory phase of a normal endometrium. hBiot2 was expressed mainly in the parenchymal cells. CONCLUSIONS: Three shearings of hBiot2 may suggest that it has different functions in different organs. The expression difference of hBiot2 between infants and adults, cancerous and normal tissues, different histological gradings in endometrial cancer, different stages during the menstrual cycle in the normal endometrium suggests that hBiot2 may have the potential to induce carcinogenesis in endometrial cancer.
