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Assessment of vascular invasion in gastric cancer: A comparative study

World Journal of Gastroenterology 2013年第24期19卷 3761-3769页

作者： letícia trivellato gresta Ismael Alves Rodrigues-Júnior Lúcia Porto Fonseca de Castro Geovanni Dantas Cassali Mnica Maria Demas lva-res Cabral Department of Anatomic Pathology and Medicine University Federal of Minas GeraisBelo Horizonte 30130-100 Brazil Institute of Biological Sciences University Federal of Minas GeraisBelo Horizonte 31270-901 Brazil

AIM: To evaluate and compare detection of lymphatic and blood vessel invasion (LVI and BVI) by hematox-ylin-eosin (HE) and immunohistochemistry (IHC) in gastric cancer specimens, and to correlate with lymph node status. METHODS: IHC using D2-40 (a lymphatic endothelial marker) and CD34 (a pan-endothelial marker) was performed to study LVI and BVI in surgical specimens froma consecutive series of 95 primary gastric cancer cases. The results of the IHC study were compared with the detection by HE using McNemar test and kappa index. The morphologic features of the tumors and the presence of LVI and BVI were related to the presence of lymph node metastasis. A χ2 test was performed to obtain associations between LVI and BVI and other prognostic factors for gastric cancer. RESULTS: The detection rate of LVI was considerably higher than that of BVI. The IHC study identified eight false-positive cases and 13 false-negative cases for LVI, and 24 false-positive cases and 10 false-negative cases for BVI. The average Kappa value determined was moderate for LVI (k=0.50) and low for BVI (k=0.20). Both LVI and BVI were statistically associated with the presence of lymph node metastasis (HE: P=0.001, P=0.013, and IHC: P=0.001, P=0.019). The mor-phologic features associated with LVI were location of the tumor in the distal third of the stomach (P=0.039), Borrmann's macroscopic type (P=0.001), organ inva-sion (P=0.03) and the depth of tumor invasion (P=0.001). The presence of BVI was related only to the depth of tumor invasion (P=0.003). CONCLUSION: The immunohistochemical identification of lymphatic and blood vessels is useful for increasing the accuracy of the diagnosis of vessel invasion and for predicting lymph node metastasis.

关键词： Gastric cancer Tumour-node-metastesis staging Lymph node metastasis Predictive factor Lymphatic vessel invasion Blood vessel invasion Immunohistochemistry CD34 D2-40

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Pattern Recognition for Flank Eruption Forecasting: An Application at Mount Etna Volcano (Sicily, Italy)

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Open Journal of Geology 2016年第7期6卷 583-597页

作者： A. Brancato P. M. Buscema G. Massini S. gresta Istituto Nazionale di Geofisica e Vulcanologia-Osservatorio Etneo Piazza Roma Catania Italy Semeion Research Center of Sciences of Communication Via Sersale Roma Italy Department of Mathematical and Statistical Sciences University of Colorado Denver CO USA Dipartimento di Scienze Biologiche Geologiche e Ambientali Sezione di Scienze della Terra Università di Catania Catania Italy

A volcano can be defined as a complex system, not least for the hidden clues related to its internal nature. Innovative models grounded in the Artificial Sciences, have been proposed for a novel pattern recognition analysis at Mt. Etna volcano. The reference monitoring dataset dealt with real data of 28 parameters collected between January 2001 and April 2005, during which the volcano underwent the July-August 2001, October 2002-January 2003 and September 2004-April 2005 flank eruptions. There were 301 eruptive days out of an overall number of 1581 investigated days. The analysis involved successive steps. First, the TWIST algorithm was used to select the most predictive attributes associated with the flank eruption target. During his work, the algorithm TWIST selected 11 characteristics of the input vector: among them SO2 and CO2 emissions, and also many other attributes whose linear correlation with the target was very low. A 5 × 2 Cross Validation protocol estimated the sensitivity and specificity of pattern recognition algorithms. Finally, different classification algorithms have been compared to understand if this pattern recognition task may have suitable results and which algorithm performs best. Best results (higher than 97% accuracy) have been obtained after performing advanced Artificial Neural Networks, with a sensitivity and specificity estimates over 97% and 98%, respectively. The present analysis highlights that a suitable monitoring dataset inferred hidden information about volcanic phenomena, whose highly non-linear processes are enhanced.

关键词： Mt. Etna Volcano Flank Eruption Forecasting Neural Networks Pattern Recognition Monitoring Data

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埃特纳火山的地震学研究回顾

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地震科技情报 1995年第10期 26-33页

作者： gresta,S 王景来

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