AIM： TO investigate the characteristics and diagnostic value of annexin A2 （ANXA2） expression in cancerous tissues and sera of patients with hepatitis B virus （HBV）-related hepatocellular carcinoma （HCC）. METH...AIM： TO investigate the characteristics and diagnostic value of annexin A2 （ANXA2） expression in cancerous tissues and sera of patients with hepatitis B virus （HBV）-related hepatocellular carcinoma （HCC）. METHODS： Levels of liver ANXA2 gene transcription or protein expression were analyzed in HCC-, their self- controlled precancerous-, and distant cancerous- tissues from 30 HCC. Serum levels of ANXA2 expression in 115 patients with HCC, 25 with metastatic liver can cer, 35 with chronic hepatitis, 28 with acute hepatitis, 38 with cirrhosis, and 30 healthy controls were deter- mined. Clinicopathological characteristics of circulating ANXA2 expression were analyzed, and its diagnostic efficiency and clinical values in HCC were evaluated. RESULTS： ANXA2 expression was localized in both cell membrane and cytoplasm in HCC tissue, mainly in the cytoplasm of matched adjacent cancerous tissue, and there was almost no positive staining in matched distant cancerous tissue. Abnormal expression of liver ANXA2 was present in HCC tissues compared with self-con- trolled adjacent- and distant-cancerous tissues at pro- tein or mRNA level. Circulating ANXA2 in HCC patients was significantly higher than that of other liver diseases （P 〈 0.01） except metastatic liver cancer. If the diag- nostic cutoff value of ANXA2 level was more than 18 ng/ mL, the incidence of serum ANXA2 was 86.96% in the HCC group, 80% in the metastatic liver cancer group, 31.58% in the liver cirrhosis group, none in the chronic hepatitis or acute hepatitis or normal control group, respectively. Serum ANXA2 expression in HCC patients was correlated with HBV infection （27.38 ± 5.67 ng/mL vs 18.58 ± 7.83 ng/mL, P 〈 0.01）, extrahepatic metas- tasis （26.11±5.43 ng/mL ys 22.79 ± 5.64 ng/mL, P 〈 0.01）, and portal vein thrombus （26.03 ± 5.99 ng/mL vs 23.06 ± 5.03 ng/mL, P 〈 0.01）, and was significantly higher （P 〈 0.01） in the moderately- （26.19±5.34 ng/ mL） or the poorly- differentiated group （27.05 ± 5.13 ng/mL） than in the well differentiated group （20.43 ± 4.97 ng/mL）, and in the tumor node metastasis stages Ⅲ-Ⅳ（P 〈 0.01） than in stages Ⅰ-Ⅱ. ANXA2 was not correlated with patient sex, age, size or α-fetoprotein （AFP） level. Area under the receiver operating charac- teristic curve for the whole range of sensitivities and specificities was 0.796 for ANXA2 and 0.782 for AFP. Combining detection of serum ANXA2 and AFP substan- tially improved the diagnostic efficiency （96.52%） and the neclative predictive value （＇96.61%） for HCC.of ANXA2 expression has good diagnostic potential for HCC diagnosis.展开更多
Partial eigenvalue decomposition(PEVD) and partial singular value decomposition(PSVD) of large sparse matrices are of fundamental importance in a wide range of applications, including latent semantic indexing, spectra...Partial eigenvalue decomposition(PEVD) and partial singular value decomposition(PSVD) of large sparse matrices are of fundamental importance in a wide range of applications, including latent semantic indexing, spectral clustering, and kernel methods for machine learning. The more challenging problems are when a large number of eigenpairs or singular triplets need to be computed. We develop practical and efficient algorithms for these challenging problems. Our algorithms are based on a filter-accelerated block Davidson method.Two types of filters are utilized, one is Chebyshev polynomial filtering, the other is rational-function filtering by solving linear equations. The former utilizes the fastest growth of the Chebyshev polynomial among same degree polynomials; the latter employs the traditional idea of shift-invert, for which we address the important issue of automatic choice of shifts and propose a practical method for solving the shifted linear equations inside the block Davidson method. Our two filters can efficiently generate high-quality basis vectors to augment the projection subspace at each Davidson iteration step, which allows a restart scheme using an active projection subspace of small dimension. This makes our algorithms memory-economical, thus practical for large PEVD/PSVD calculations. We compare our algorithms with representative methods, including ARPACK, PROPACK, the randomized SVD method, and the limited memory SVD method. Extensive numerical tests on representative datasets demonstrate that, in general, our methods have similar or faster convergence speed in terms of CPU time, while requiring much lower memory comparing with other methods. The much lower memory requirement makes our methods more practical for large-scale PEVD/PSVD computations.展开更多
基金Supported by Priority Academic Program Development of Jiangsu Higher Education Institution (PAPD)the Project of Jiangsu Clinical Medicine (BL2012053)+1 种基金the Programs of Nantong Society Undertaking and Technological Innovation,No.HS2012034 and HS2011012the International S and T Cooperation Program of China
文摘AIM： TO investigate the characteristics and diagnostic value of annexin A2 （ANXA2） expression in cancerous tissues and sera of patients with hepatitis B virus （HBV）-related hepatocellular carcinoma （HCC）. METHODS： Levels of liver ANXA2 gene transcription or protein expression were analyzed in HCC-, their self- controlled precancerous-, and distant cancerous- tissues from 30 HCC. Serum levels of ANXA2 expression in 115 patients with HCC, 25 with metastatic liver can cer, 35 with chronic hepatitis, 28 with acute hepatitis, 38 with cirrhosis, and 30 healthy controls were deter- mined. Clinicopathological characteristics of circulating ANXA2 expression were analyzed, and its diagnostic efficiency and clinical values in HCC were evaluated. RESULTS： ANXA2 expression was localized in both cell membrane and cytoplasm in HCC tissue, mainly in the cytoplasm of matched adjacent cancerous tissue, and there was almost no positive staining in matched distant cancerous tissue. Abnormal expression of liver ANXA2 was present in HCC tissues compared with self-con- trolled adjacent- and distant-cancerous tissues at pro- tein or mRNA level. Circulating ANXA2 in HCC patients was significantly higher than that of other liver diseases （P 〈 0.01） except metastatic liver cancer. If the diag- nostic cutoff value of ANXA2 level was more than 18 ng/ mL, the incidence of serum ANXA2 was 86.96% in the HCC group, 80% in the metastatic liver cancer group, 31.58% in the liver cirrhosis group, none in the chronic hepatitis or acute hepatitis or normal control group, respectively. Serum ANXA2 expression in HCC patients was correlated with HBV infection （27.38 ± 5.67 ng/mL vs 18.58 ± 7.83 ng/mL, P 〈 0.01）, extrahepatic metas- tasis （26.11±5.43 ng/mL ys 22.79 ± 5.64 ng/mL, P 〈 0.01）, and portal vein thrombus （26.03 ± 5.99 ng/mL vs 23.06 ± 5.03 ng/mL, P 〈 0.01）, and was significantly higher （P 〈 0.01） in the moderately- （26.19±5.34 ng/ mL） or the poorly- differentiated group （27.05 ± 5.13 ng/mL） than in the well differentiated group （20.43 ± 4.97 ng/mL）, and in the tumor node metastasis stages Ⅲ-Ⅳ（P 〈 0.01） than in stages Ⅰ-Ⅱ. ANXA2 was not correlated with patient sex, age, size or α-fetoprotein （AFP） level. Area under the receiver operating charac- teristic curve for the whole range of sensitivities and specificities was 0.796 for ANXA2 and 0.782 for AFP. Combining detection of serum ANXA2 and AFP substan- tially improved the diagnostic efficiency （96.52%） and the neclative predictive value （＇96.61%） for HCC.of ANXA2 expression has good diagnostic potential for HCC diagnosis.
基金supported by National Science Foundation of USA (Grant Nos. DMS1228271 and DMS-1522587)National Natural Science Foundation of China for Creative Research Groups (Grant No. 11321061)+1 种基金the National Basic Research Program of China (Grant No. 2011CB309703)the National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences
文摘Partial eigenvalue decomposition(PEVD) and partial singular value decomposition(PSVD) of large sparse matrices are of fundamental importance in a wide range of applications, including latent semantic indexing, spectral clustering, and kernel methods for machine learning. The more challenging problems are when a large number of eigenpairs or singular triplets need to be computed. We develop practical and efficient algorithms for these challenging problems. Our algorithms are based on a filter-accelerated block Davidson method.Two types of filters are utilized, one is Chebyshev polynomial filtering, the other is rational-function filtering by solving linear equations. The former utilizes the fastest growth of the Chebyshev polynomial among same degree polynomials; the latter employs the traditional idea of shift-invert, for which we address the important issue of automatic choice of shifts and propose a practical method for solving the shifted linear equations inside the block Davidson method. Our two filters can efficiently generate high-quality basis vectors to augment the projection subspace at each Davidson iteration step, which allows a restart scheme using an active projection subspace of small dimension. This makes our algorithms memory-economical, thus practical for large PEVD/PSVD calculations. We compare our algorithms with representative methods, including ARPACK, PROPACK, the randomized SVD method, and the limited memory SVD method. Extensive numerical tests on representative datasets demonstrate that, in general, our methods have similar or faster convergence speed in terms of CPU time, while requiring much lower memory comparing with other methods. The much lower memory requirement makes our methods more practical for large-scale PEVD/PSVD computations.
