The role of circadian clocks in cancer: Mechanisms and clinical implications

Circadian rhythm refers to the inherent 24-h cycle oscillation of biochemical, physiological and behavioral functions, which is almost universal in eukaryotes. At least 14 core clock genes have been reported to form multiple chain feedback loops that confer intrinsic circadian rhythmicity onto the molecular clock. Accumulating evidence has shown that the circadian gene dysfunction resulted from single nucleotide polymorphisms (SNPs), deletions, epigenetic modification, and deregulation is strongly associated with cancer risk. In the present review, we describe the composition of circadian rhythm system. We highlight the function and mechanism of clock genes in cancer pathogenesis and progression. Moreover, their potential clinical implications as prognostic biomarkers and therapeutic targets have been addressed

A three-level framework for affective content analysis and its case studies

Emotional factors directly reflect audiences' attention, evaluation and memory. Recently, video affective content analysis attracts more and more research efforts. Most of the existing methods map low-level affective features directly to emotions by applying machine learning. Compared to human perception process, there is actually a gap between low-level features and high-level human perception of emotion. In order to bridge the gap, we propose a three-level affective content analysis framework by introducing mid-level representation to indicate dialog, audio emotional events (e.g., horror sounds and laughters) and textual concepts (e.g., informative keywords). Mid-level representation is obtained from machine learning on low-level features and used to infer high-level affective content. We further apply the proposed framework and focus on a number of case studies. Audio emotional event, dialog and subtitle are studied to assist affective content detection in different video domains/genres. Multiple modalities are considered for affective analysis, since different modality has its own merit to evoke emotions. Experimental results shows the proposed framework is effective and efficient for affective content analysis. Audio emotional event, dialog and subtitle are promising mid-level representations

Hierarchical affective content analysis in arousal and valence dimensions

Different from the existing work focusing on emotion type detection, the proposed approach in this paper provides flexibility for users to pick up their favorite affective content by choosing either emotion intensity levels or emotion types. Specifically, we propose a hierarchical structure for movie emotions and analyze emotion intensity and emotion type by using arousal and valence related features hierarchically. Firstly, three emotion intensity levels are detected by using fuzzy c-mean clustering on arousal features. Fuzzy clustering provides a mathematical model to represent vagueness, which is close to human perception. Then, valence related features are used to detect five emotion types. Considering video is continuous time series data and the occurrence of a certain emotion is affected by recent emotional history, conditional random fields (CRFs) are used to capture the context information. Outperforming Hidden Markov Model, CRF relaxes the independence assumption for states required by HMM and avoids bias problem. Experimental results show that CRF-based hierarchical method outperforms the one-step method on emotion type detection. User study shows that majority of the viewers prefer to have option of accessing movie content by emotion intensity levels. Majority of the users are satisfied with the proposed emotion detection

Automatic liver parenchyma segmentation from abdominal CT images using support vector machines

This paper presents an automatic liver parenchyma segmentation algorithm that can segment liver in abdominal CT images. There are three major steps in the proposed approach. Firstly, a texture analysis is applied to input abdominal CT images to extract pixel level features. In this step, wavelet coefficients are used as texture descriptors. Secondly, support vector machines (SVMs) are implemented to classify the data into pixel-wised liver area or non-liver area. Finally, integrated morphological operations are designed to remove noise and finally delineate the liver. Our unique contributions to liver segmentation are twofold: one is that it has been proved through experiments that wavelet features present good classification result when SVMs are used; the other is that the combination of morphological operations with the pixel-wised SVM classifier can delineate volumetric liver accurately. The algorithm can be used in an advanced computer-aided liver disease diagnosis and liver surgical planning system. Examples of applying the proposed algorithm on real CT data are presented with performance validation based on the comparison between the automatically segmented results and manually segmented ones

Design and optimization of a novel compliant planar parallelogram mechanism utilizing initially curved beams

International audienc

Emerging roles of lipid metabolism in cancer metastasis

Abstract Cancer cells frequently display fundamentally altered cellular metabolism, which provides the biochemical foundation and directly contributes to tumorigenicity and malignancy. Rewiring of metabolic programmes, such as aerobic glycolysis and increased glutamine metabolism, are crucial for cancer cells to shed from a primary tumor, overcome the nutrient and energy deficit, and eventually survive and form metastases. However, the role of lipid metabolism that confers the aggressive properties of malignant cancers remains obscure. The present review is focused on key enzymes in lipid metabolism associated with metastatic disease pathogenesis. We also address the function of an important membrane structure-lipid raft in mediating tumor aggressive progression. We enumerate and integrate these recent findings into our current understanding of lipid metabolic reprogramming in cancer metastasis accompanied by new and exciting therapeutic implications