Multi-Label Zero-Shot Learning with Structured Knowledge Graphs

In this paper, we propose a novel deep learning architecture for multi-label zero-shot learning (ML-ZSL), which is able to predict multiple unseen class labels for each input instance. Inspired by the way humans utilize semantic knowledge between objects of interests, we propose a framework that incorporates knowledge graphs for describing the relationships between multiple labels. Our model learns an information propagation mechanism from the semantic label space, which can be applied to model the interdependencies between seen and unseen class labels. With such investigation of structured knowledge graphs for visual reasoning, we show that our model can be applied for solving multi-label classification and ML-ZSL tasks. Compared to state-of-the-art approaches, comparable or improved performances can be achieved by our method.Comment: CVPR 201

Metabolic syndrome and abdominal fat are associated with inflammation, but not with clinical outcomes, in peritoneal dialysis patients

BACKGROUND: In the general population, metabolic syndrome (MetS) is correlated with visceral fat and a risk factor for cardiovascular disease (CVD); however, little is known about the significance of abdominal fat and its association with inflammation and medication use in peritoneal dialysis (PD) patients. We investigated the relationship of visceral fat area (VFA) with C-reactive protein (CRP) levels and medication use in PD patients and followed their clinical outcomes. METHODS: In a prospective study from February 2009 to February 2012, we assessed diabetes mellitus (DM) status, clinical and PD-associated characteristics, medication use, CRP levels, components of MetS, and VFA in 183 PD patients. These patients were categorized into 3 groups based on MetS and DM status: non-MetS (group 1, n = 73), MetS (group 2, n = 65), and DM (group 3, n = 45). VFA was evaluated by computed tomography (CT) and corrected for body mass index (BMI). RESULTS: Patients in group 1 had smaller VFAs than patients in groups 2 and 3 (3.2 ± 1.8, 4.6 ± 1.9, and 4.9 ± 2.0 cm(2)/[kg/m(2)], respectively, P < 0.05) and lower CRP levels (0.97 ± 2.31, 1.27 ± 2.57, and 1.11 ± 1.35 mg/dL, respectively, P < 0.05). VFA increased with the number of criteria met for MetS. After adjusting for age, body weight, and sex, CRP and albumin levels functioned as independent positive predictors of VFA; on other hand, the use of renin-angiotensin system blockers was inversely correlated with VFA in PD patients without DM. In the survival analysis, DM patients (group 3) had the poorest survival among the 3 groups, but no significant differences were found between groups 1 and 2. CONCLUSION: This study showed that VFA and MetS are associated with CRP levels but cannot predict survival in PD patients without DM. The complex relationship of nutritional parameters to VFA and MetS may explain these results. The type of antihypertensive medication used was also associated with the VFA. The mechanisms behind these findings warrant further investigation

Integration of Genetic Programming and TABU Search Mechanism for Automatic Detection of Magnetic Resonance Imaging in Cervical Spondylosis

Cervical spondylosis is a kind of degenerative disease which not only occurs in elder patients. The age distribution of patients is unfortunately decreasing gradually. Magnetic Resonance Imaging (MRI) is the best tool to confirm the cervical spondylosis severity but it requires radiologist to spend a lot of time for image check and interpretation. In this study, we proposed a prediction model to evaluate the cervical spine condition of patients by using MRI data. Furthermore, to ensure the computing efficiency of the proposed model, we adopted a heuristic programming, genetic programming (GP), to build the core of refereeing engine by combining the TABU search (TS) with the evolutionary GP. Finally, to validate the accuracy of the proposed model, we implemented experiments and compared our prediction results with radiologist’s diagnosis to the same MRI image. The experiment found that using clinical indicators to optimize the TABU list in GP+TABU got better fitness than the other two methods and the accuracy rate of our proposed model can achieve 88% on average. We expected the proposed model can help radiologists reduce the interpretation effort and improve the relationship between doctors and patients

Molecular population genetics and gene expression analysis of duplicated CBF genes of Arabidopsis thaliana

<p>Abstract</p> <p>Background</p> <p><it>CBF/DREB </it>duplicate genes are widely distributed in higher plants and encode transcriptional factors, or CBFs, which bind a DNA regulatory element and impart responsiveness to low temperatures and dehydration.</p> <p>Results</p> <p>We explored patterns of genetic variations of <it>CBF1, -2</it>, and -<it>3 </it>from 34 accessions of <it>Arabidopsis thaliana</it>. Molecular population genetic analyses of these genes indicated that <it>CBF2 </it>has much reduced nucleotide diversity in the transcriptional unit and promoter, suggesting that <it>CBF2 </it>has been subjected to a recent adaptive sweep, which agrees with reports of a regulatory protein of <it>CBF2</it>. Investigating the ratios of K_a/K_sbetween all paired <it>CBF </it>paralogus genes, high conservation of the AP2 domain was observed, and the major divergence of proteins was the result of relaxation in two regions within the transcriptional activation domain which was under positive selection after <it>CBF </it>duplication. With respect to the level of <it>CBF </it>gene expression, several mutated nucleotides in the promoters of <it>CBF3 </it>and <it>-1 </it>of specific ecotypes might be responsible for its consistently low expression.</p> <p>Conclusion</p> <p>We concluded from our data that important evolutionary changes in <it>CBF1, -2</it>, and -<it>3 </it>may have primarily occurred at the level of gene regulation as well as in protein function.</p

The Inhibitory Effect of Ellagic Acid on Cell Growth of Ovarian Carcinoma Cells

Ellagic acid (EA) is able to inhibit the growth of several cancer cells; however, its effect on human ovarian carcinoma cells has not yet been investigated. Ovarian carcinoma ES-2 and PA-1 cells were treated with EA (10~100 μM) and assessed for viability, cell cycle, apoptosis, anoikis, autophagy, and chemosensitivity to doxorubicin and their molecular mechanisms. EA inhibited cell proliferation in a dose- and time-dependent manner by arresting both cell lines at the G1 phase of the cell cycle, which were from elevating p53 and Cip1/p21 and decreasing cyclin D1 and E levels. EA also induced caspase-3-mediated apoptosis by increasing the Bax : Bcl-2 ratio and restored anoikis in both cell lines. The enhancement of apoptosis and/or inhibition of autophagy in these cells by EA assisted the chemotherapy efficacy. The results indicated that EA is a potential novel chemoprevention and treatment assistant agent for human ovarian carcinoma