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Lan Y.,Huaihai Institute of Technology | Ren H.,Huaihai Institute of Technology | Wan J.,Lianyungang Second Peoples Hospital
Proceedings - 4th International Conference on Computational and Information Sciences, ICCIS 2012

Breast cancer is a very deadly disease for women. For the time being, mammographic screening remains the most effective method for early detection of breast cancer. However, reading mammography is a time-consume error-prone work. Therefore, many computer-aided detection and diagnosis systems (CAD) have been developed to assist radiologists in detecting and classifying mammographic mass. Most of those CAD system used single classifier for the classification of mass patterns into benign and malignant, or normal and mass or calcification. Increasing number of researches demonstrated that multi-classifier is an effective approach to improve the classification performance of CAD system. In this paper, we present a new hybrid classifier for mammographic CAD by hybridizing Logistic Regression (LR) and K-nearest neighbor (KNN) classifiers. To test and evaluate the proposed hybrid classifier, several experiments were carried out. The experimental results show that the proposed hybrid method achieves better performance then those two single classifiers (i.e., LR classifier and KNN classifier). © 2012 IEEE. Source

Wan J.,Lianyungang Second Peoples Hospital | Lan Y.,Nanyang Normal University | Zhao R.,Huazhong University of Science and Technology
Proceedings - 2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2013

Mass segmentation is a very important step in most computer-aided diagnosis (CAD) systems for classification of suspicious regions as normal, benign or malignant. Although a lot of algorithms have been proposed for mass segmentation in mammography, accurate segmentation is still a challenge. In this article, a global optimal active contour model was applied to mammography masses segmentation. Variational method was employed to solve it. At last, a lot of experiments were carried out to demonstrate the effeteness of the proposed hybrid method. © 2013 IEEE. Source

Ruan L.,Wenzhou University | Chen R.,Wenzhou University | Wang R.,Taizhou Institution for Food and Drug Control | Xie X.,Wenzhou University | And 9 more authors.
Metabolic Brain Disease

The lifetime prevalence rate for major depressive disorder (MDD) is approximately 17 % for most developed countries around the world. Dietary polyphenols are currently used as an adjuvant therapy to accelerate the therapeutic efficacy on depression. Ferulic acid (FA) or 4-hydroxy-3-methoxy-cinnamic acid (Fig. 1a) is a main polyphenolic component of Chinese herb Radix Angelicae Sinensis, which is found to have antidepressant-like effects through regulating serotonergic and noradrenergic function. The present study examined the synergistic effect of low doses of FA combined with subthreshold dose of piperine, a bioavailability enhancer, on depression-like behaviors in mice, and investigated the possible mechanism. The administration of FA, even in the highest dose tested, reduced immobility time by 60 % in the tail suspension and forced swimming tests (TST and FST) in mice when compared to control. The maximal antidepressant-like effect of FA was obtained with 200 mg/kg. In addition, piperine only produced a weak antidepressant-like effect in the TST and FST. However, the evidence from the interaction analysis suggested a synergistic effect when low doses of FA were combined with a subthreshold dose of piperine. Further neurochemical evidence such as monoamine levels in the frontal cortex, hippocampus, and hypothalamus and measurements of monoamine oxidase activity also supported a synergistic effect of FA and piperine in the enhancement of monoaminergic function. This finding supports the concept that the combination strategy might be an alternative therapy in the treatment of psychiatric disorders with high efficacy and low side effects. © 2015, Springer Science+Business Media New York. Source

Fan G.-H.,Nanjing Medical University | Wang Z.-M.,Nanjing Medical University | Yang X.,Nanjing Medical University | Xu L.-P.,Nanjing Medical University | And 5 more authors.
Asian Pacific Journal of Cancer Prevention

Resveratrol has been examined in several model systems for potential effects against cancer. Adenosine monophosphate-activated protein kinase (AMPK) is reported to suppress proliferation in most eukaryocyte cells. Whether resveratrol via AMPK inhibits proliferation of oesophageal adenocarcinoma cells (OAC) is unknown. The aim of this study was to determine the roles of AMPK in the protective effects of resveratrol in OAC proliferation and to elucidate the underlying mechanisms. Treatment of cultured OAC derived from human subjects or cell lines with resveratrol resulted in decreased cell proliferation. Further, inhibition of AMPK by pharmacological reagent or genetical approach abolished resveratrol-suppressed OAC proliferation, reduced the level of P27Kip1, a cyclin-dependent kinase inhibitor, and increased the levels of S-phase kinase-associated protein 2 (Skp2) of P27Kip1-E3 ubiquitin ligase and 26S proteasome activity reduced by resveratrol. Furthermore, gene silencing of P27Kip1 reversed resveratrol-suppressed OAC proliferation. In conclusion, these findings indicate that resveratrol inhibits Skp2-mediated ubiquitylation and 26S proteasome-dependent degradation of P27Kip1 via AMPK activation to suppress OAC proliferation. Source

Lan Y.,Nanyang Normal University | Ren H.,Huaihai Institute of Technology | Li C.,Huaihai Institute of Technology | Min Z.,Huazhong Institute of Optoelectronics | And 3 more authors.
Technology in Cancer Research and Treatment

In order to facilitate the leaf sequencing process in intensity modulated radiation therapy (IMRT), and design of a practical leaf sequencing algorithm, it is an important issue to smooth the planned fluence maps. The objective is to achieve both high-efficiency and high-precision dose delivering by considering characteristics of leaf sequencing process. The key factor which affects total number of monitor units for the leaf sequencing optimization process is the max flow value of the digraph which formulated from the fluence maps. Therefore, we believe that one strategy for compromising dose conformity and total number of monitor units in dose delivery is to balance the dose distribution function and the max flow value mentioned above. However, there are too many paths in the digraph, and we don't know the flow value of which path is the maximum. The maximum flow value among the horizontal paths was selected and used in the objective function of the fluence map optimization to formulate the model. The model is a traditional linear constrained quadratic optimization model which can be solved by interior point method easily. We believe that the smoothed maps from this model are more suitable for leaf sequencing optimization process than other smoothing models. A clinical head-neck case and a prostate case were tested and compared using our proposed model and the smoothing model which is based on the minimization of total variance. The optimization results with the same level of total number of monitor units (TNMU) show that the fluence maps obtained from our model have much better dose performance for the target/non-target region than the maps from total variance based on the smoothing model. This indicates that our model achieves better dose distribution when the algorithm suppresses the TNMU at the same level. Although we have just used the max flow value of the horizontal paths in the diagraph in the objective function, a good balance has been achieved between the dose conformity and the total number of monitor units. This idea can be extended to other fluence map optimization model, and we believe it can also achieve good performance. © Adenine Press (2013). Source

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