Hepatocellular carcinoma (HCC) is the third largest cause of cancer deaths worldwide. The role of molecular changes in HCC have been used to identify prognostic markers and chemopreventive or therapeutic targets. It s...
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Hepatocellular carcinoma (HCC) is the third largest cause of cancer deaths worldwide. The role of molecular changes in HCC have been used to identify prognostic markers and chemopreventive or therapeutic targets. It seems that toll-like receptors (TLRs) as well as the nuclear factor (NF)-kappa B, and JNK pathways are critical regulators for the production of the cytokines associated with tumor promotion. The cross-talk between an inflammatory cell and a neoplastic cell, which is instigated by the activation of NF-kappa B and JNKs, is critical for tumor organization. JNKs also regulate cell proliferation and act as oncogenes, making them the main tumor-promoting protein kinases. TLRs play roles in cytokine and hepatomitogen expression mainly in myeloid cells and may promote liver tumorigenesis. A better understanding of these signaling pathways in the liver will help us understand the mechanism of hepatocarcinogenesis and provide a new therapeutic target for HCC.
Background and Aims. An arterial blood supply and phenotypic changes of the sinusoids characterise the liver vasculature in human hepatocellular carcinoma (HCC). We investigated the effects of rosuvastatin on liver ve...
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Background and Aims. An arterial blood supply and phenotypic changes of the sinusoids characterise the liver vasculature in human hepatocellular carcinoma (HCC). We investigated the effects of rosuvastatin on liver vessel anomalies, tumour growth and survival in HCC. Methods. We treated transgenic mice developing HCC, characterized by vessel anomalies similar to those of human HCC, with rosuvastatin. Results. In the rosuvastatin group, the survival time was longer (P < .001), and liver weight (P < .01) and nodule surface (P < .01) were reduced. Rosuvastatin decreased the number of smooth muscle actin-positive arteries (P < .05) and prevented the sinusoid anomalies, with decreased laminin expression (P < .001), activated hepatic stellate cells (P < .001), and active Notch4 expression. Furthermore, rosuvastatin inhibited endothelial cell but not tumour hepatocyte functions. Conclusions. Rosuvastatin reduced the vessel anomalies and tumour growth and prolonged survival in HCC. These results represent new mechanisms of the effects of statin on tumour angiogenesis and a potential target therapy in HCC.
I READ WITH great interest the article by Weber A et al. The article reports important outcomes for cirrhotic patients and portal vein thrombosis (PVT). The authors retrospectively evaluated 236 patients. They exclude...
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I READ WITH great interest the article by Weber A et al. The article reports important outcomes for cirrhotic patients and portal vein thrombosis (PVT). The authors retrospectively evaluated 236 patients. They excluded 148 patients and the data of 88 patients were analysed. They stated the significant difference of international normalized ratio (INR) and activated partial thrombo-plastin time (aPTT) in Child scores A, B and C cirrhosis. As we already know, the risk of PVT increases with severity of cirrhosis, and, hepatocellular carcinoma (HCC) is the most common risk factor. That is why, I think, the exclusion of HCC patients in the study group may have resulted in misleading conclusions being drawn.
Due to the increasing availability and sophistication of data recording techniques, multiple information sources and distributed computing are becoming the important trends of modern information systems. Many applicat...
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Due to the increasing availability and sophistication of data recording techniques, multiple information sources and distributed computing are becoming the important trends of modern information systems. Many applications such as security informatics and social computing require a ubiquitous data analysis platform so that decisions can be made rapidly under distributed and dynamic system environments. Although data mining has now been popularly used to achieve such goals, building a data mining system is, however, a nontrivial task, which may require a complete understanding on numerous data mining techniques as well as solid programming skills. Employing agent techniques for data analysis thus becomes increasingly important, especially for users not familiar with engineering and computational sciences, to implement an effective ubiquitous mining platform. Such data mining agents should, in practice, be intelligent, complete, and compact. In this paper, we present an interactive data mining agent - OIDM (online interactive data mining), which provides three categories (classification, association analysis, and clustering) of data mining tools, and interacts with the user to facilitate the mining process. The interactive mining is accomplished through interviewing the user about the data mining task to gain efficient and intelligent data mining control. OIDM can help users find appropriate mining algorithms, refine and compare the mining process, and finally achieve the best mining results. Such interactive data mining agent techniques provide alternative solutions to rapidly deploy data mining techniques to broader areas of data intelligence and knowledge informaties.
Automated analysis of human affective behavior has attracted increasing attention from researchers in psychology, computer science, linguistics, neuroscience, and related disciplines. However, the existing methods typ...
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Automated analysis of human affective behavior has attracted increasing attention from researchers in psychology, computer science, linguistics, neuroscience, and related disciplines. However, the existing methods typically handle only deliberately displayed and exaggerated expressions of prototypical emotions, despite the fact that deliberate behavior differs in visual appearance, audio profile, and timing from spontaneously occurring behavior. To address this problem, efforts to develop algorithms that can process naturally occurring human affective behavior have recently emerged. Moreover, an increasing number of efforts are reported toward multimodal fusion for human affect analysis, including audiovisual fusion, linguistic and paralinguistic fusion, and multicue visual fusion based on facial expressions, head movements, and body gestures. This paper introduces and surveys these recent advances. We first discuss human emotion perception from a psychological perspective. Next, we examine available approaches for solving the problem of machine understanding of human affective behavior and discuss important issues like the collection and availability of training and test data. We finally outline some of the scientific and engineering challenges to advancing human affect sensing technology.
A challenge in facilitating spontaneous mobile interactions is to provide pairing methods that are both intuitive and secure. Simultaneous shaking is proposed as a novel and easy-to-use mechanism for pairing of small ...
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A challenge in facilitating spontaneous mobile interactions is to provide pairing methods that are both intuitive and secure. Simultaneous shaking is proposed as a novel and easy-to-use mechanism for pairing of small mobile devices. The underlying principle is to use common movement as a secret that the involved devices share for mutual authentication. We present two concrete methods, ShaVe and ShaCK, in which sensing and analysis of shaking movement is combined with cryptographic protocols for secure authentication. ShaVe is based on initial key exchange followed by exchange and comparison of sensor data for verification of key authenticity. ShaCK, in contrast, is based on matching features extracted from the sensor data to construct a cryptographic key. The classification algorithms used in our approach are shown to robustly separate simultaneous shaking of two devices from other concurrent movement of a pair of devices, with a false negative rate of under 12 percent. A user study confirms that the method is intuitive and easy to use, as users can shake devices in an arbitrary pattern.
This paper addresses the problem of learning situation models for providing context-aware services. Context for modeling human behavior in a smart environment is represented by a situation model describing environment...
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This paper addresses the problem of learning situation models for providing context-aware services. Context for modeling human behavior in a smart environment is represented by a situation model describing environment, users, and their activities. A framework for acquiring and evolving different layers of a situation model in a smart environment is proposed. Different learning methods are presented as part of this framework: role detection per entity, unsupervised extraction of situations from multimodal data, supervised learning of situation representations, and evolution of a predefined situation model with feedback. The situation model serves as frame and support for the different methods, permitting to stay in an intuitive declarative framework. The proposed methods have been integrated into a whole system for smart home environment. The implementation is detailed, and two evaluations are conducted in the smart home environment. The obtained results validate the proposed approach.
Individual emotions play a crucial role during any learning interaction. Identifying a student's emotional state and providing personalized feedback, based on integrated pedagogical models, has been considered to ...
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Individual emotions play a crucial role during any learning interaction. Identifying a student's emotional state and providing personalized feedback, based on integrated pedagogical models, has been considered to be one of the main limits of traditional tools of e-learning. This paper presents an empirical study that illustrates how learner mood may be predicted during online self-assessment tests. Here, a previous method of determining student mood has been refined based on the assumption that the influence on learner mood of questions already answered declines in relation to their distance from the current question. Moreover, this paper sets out to indicate that "exponential logic" may help produce more efficient models if integrated adequately with affective modeling. The results show that these assumptions may prove useful to future research.
This study evaluated whether hepatic resection is a reasonable strategy as an initial treatment for hepatocellular carcinoma (HCC) meeting Milan criteria in patients with compensated cirrhosis. From the database of 43...
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This study evaluated whether hepatic resection is a reasonable strategy as an initial treatment for hepatocellular carcinoma (HCC) meeting Milan criteria in patients with compensated cirrhosis. From the database of 435 consecutive patients with resection of HCC between July 1994 and May 2007, 21.3 patients were found to have Child-Turcotte-Pugh class A cirrhosis and HCC meeting Milan criteria, as shown by preoperative image studies. We examined long-term survivals and patterns of recurrence after hepatic resection among those patients. Overall survival rates at 1, 3, 5, and 10 years were 92%, 78%, 69%, and 52%, respectively, and 1-, 3-, 5-, and 10-year disease-free survival rates were 79%, 57%, 44%, and 19%, respectively. Pathological review indicated that 36/213 patients (16.9%) had another nodule and/or gross vascular invasion. Microvascular invasion, tumor size, and histological grade of cirrhosis were independent risk factors for recurrence. Sixty percent of recurrent cases met the Milan criteria. The six patients who underwent living donor salvage liver transplantation (OLT) for intrahepatic recurrence were alive without recurrence at a median of 24 (range = 8-31) months. These favorable data suggest that hepatic resection is a good option for small HCCs in patients with compensated cirrhosis;and salvage OLT may be reserved for patients with recurrences.
The development of interfaces has been a technology-driven process. However, the newly developed multimodal interfaces are using recognition-based technologies that must interpret human-speech, gesture, gaze, movement...
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The development of interfaces has been a technology-driven process. However, the newly developed multimodal interfaces are using recognition-based technologies that must interpret human-speech, gesture, gaze, movement patterns, and other behavioral cues. As a result, the interface design requires a human-centered approach. In this paper we review the major approaches to multimodal human Computer Interaction, giving an overview of the user and task modeling, and of the multimodal fusion. We highlight the challenges, open issues, and the future trends in multimodal interfaces research.
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