624 research outputs found

    1997-2012: Fifteen Years of Research on Peptide Lunasin

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    Publisher under CC BY 3.0 license.Peer Reviewe

    Comparative study of an externship program versus a corporate-academic cooperation program for enhancing nursing competence of graduating students

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    BACKGROUND: New graduates report intense stress during the transition from school to their first work settings. Managing this transition is important to reduce turnover rates. This study compared the effects of an externship program and a corporate-academic cooperation program on enhancing junior college students’ nursing competence and retention rates in the first 3 months and 1 year of initial employment. METHODS: This two-phase study adopted a pretest and posttest quasi-experimental design. All participants were graduating students drawn from a 5-year junior nursing college in Taiwan. There were 19 and 24 students who participated in the phase I externship program and phase II corporate-academic cooperation program, respectively. The nursing competence of the students had to be evaluated by mentors within 48 hours of practicum training and after practicum training. The retention rate was also surveyed at 3 months and 1 year after beginning employment. RESULTS: Students who participated in the corporate-academic cooperation program achieved a statistically significant improvement in nursing competence and retention rates relative to those who participated in the externship program (p < 0.01 and p < 0.05, respectively). CONCLUSIONS: The corporate-academic cooperation program facilitates the transition of junior college nursing students into independent staff nurses, enhances their nursing competence, and boosts retention rates

    An Analysis System for Integrating High-Throughput Transcript Abundance Data with Metabolic Pathways in Green Algae

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    As the most important non-vascular plants, algae have many research applications, including high species diversity, biofuel sources, adsorption of heavy metals and, following processing, health supplements. With the increasing availability of next-generation sequencing (NGS) data for algae genomes and transcriptomes, an integrated resource for retrieving gene expression data and metabolic pathway is essential for functional analysis and systems biology in algae. However, gene expression profiles and biological pathways are displayed separately in current resources, and making it impossible to search current databases directly to identify the cellular response mechanisms. Therefore, this work develops a novel AlgaePath database to retrieve gene expression profiles efficiently under various conditions in numerous metabolic pathways. AlgaePath, a web-based database, integrates gene information, biological pathways, and next-generation sequencing (NGS) datasets in Chlamydomonasreinhardtii and Neodesmus sp. UTEX 2219-4. Users can identify gene expression profiles and pathway information by using five query pages (i.e. Gene Search, Pathway Search, Differentially Expressed Genes (DEGs) Search, Gene Group Analysis, and Co-Expression Analysis). The gene expression data of 45 and 4 samples can be obtained directly on pathway maps in C. reinhardtii and Neodesmus sp. UTEX 2219-4, respectively. Genes that are differentially expressed between two conditions can be identified in Folds Search. Furthermore, the Gene Group Analysis of AlgaePath includes pathway enrichment analysis, and can easily compare the gene expression profiles of functionally related genes in a map. Finally, Co-Expression Analysis provides co-expressed transcripts of a target gene. The analysis results provide a valuable reference for designing further experiments and elucidating critical mechanisms from high-throughput data. More than an effective interface to clarify the transcript response mechanisms in different metabolic pathways under various conditions, AlgaePath is also a data mining system to identify critical mechanisms based on high-throughput sequencing

    Deep Learning-based Fall Detection Algorithm Using Ensemble Model of Coarse-fine CNN and GRU Networks

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    Falls are the public health issue for the elderly all over the world since the fall-induced injuries are associated with a large amount of healthcare cost. Falls can cause serious injuries, even leading to death if the elderly suffers a "long-lie". Hence, a reliable fall detection (FD) system is required to provide an emergency alarm for first aid. Due to the advances in wearable device technology and artificial intelligence, some fall detection systems have been developed using machine learning and deep learning methods to analyze the signal collected from accelerometer and gyroscopes. In order to achieve better fall detection performance, an ensemble model that combines a coarse-fine convolutional neural network and gated recurrent unit is proposed in this study. The parallel structure design used in this model restores the different grains of spatial characteristics and capture temporal dependencies for feature representation. This study applies the FallAllD public dataset to validate the reliability of the proposed model, which achieves a recall, precision, and F-score of 92.54%, 96.13%, and 94.26%, respectively. The results demonstrate the reliability of the proposed ensemble model in discriminating falls from daily living activities and its superior performance compared to the state-of-the-art convolutional neural network long short-term memory (CNN-LSTM) for FD

    Emotion and Concentration Integrated System: Applied to the Detection and Analysis of Consumer Preference

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    With the expansion of consumer market, the appearance becomes an important issue when consumers make decisions under the situation of similar qualities and contents. Accordingly, to attract consumers, companies cost and take much attention on product appearance. Compared to using questionnaires individually, obtaining humans’ thoughts directly from their brains can accurately grasp the actual preference of consumers, which can provide effective and precious decisions for companies. \ In this study, consumers’ brainwaves which are related to concentration and emotion are extracted by wearing a portable and wireless Electroencephalography (EEG) device. The extracted EEG data are then trained by using perceptron learning algorithm (PLA) to make the judgments of concentration and emotion work well with each subject. They are then applied to the detection and analysis of consumer preference. Finally, the questionnaires are also performed and used as the reference on training process. They are integrated with brainwaves data to create one prediction model which can improve the accuracy significantly. The Partial Least Squares is used to compare the correlation between different factors in the model, to ensure the test can accurately meet consumers’ thoughts

    Aciculatin inhibits lipopolysaccharide-mediated inducible nitric oxide synthase and cyclooxygenase-2 expression via suppressing NF-κB and JNK/p38 MAPK activation pathways

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    <p>Abstract</p> <p>Objectives</p> <p>Natural products have played a significant role in drug discovery and development. Inflammatory mediators such as inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) have been suggested to connect with various inflammatory diseases. In this study, we explored the anti-inflammatory potential of aciculatin (8-((2<it>R</it>,4<it>S</it>,5<it>S</it>,6<it>R</it>)-tetrahydro-4,5-dihydroxy-6-methyl-2<it>H</it>-pyran-2-yl)-5-hydroxy-2-(4-hydroxyphenyl)-7-methoxy-4<it>H</it>-chromen-4-one), one of main components of <it>Chrysopogon aciculatis</it>, by examining its effects on the expression and activity of iNOS and COX-2 in lipopolysaccharide (LPS)-activated macrophages.</p> <p>Methods</p> <p>We used nitrate and prostaglandin E<sub>2 </sub>(PGE<sub>2</sub>) assays to examine inhibitory effect of aciculatin on nitric oxide (NO) and PGE<sub>2 </sub>levels in LPS-activated mouse RAW264.7 macrophages and further investigated the mechanisms of aciculatin suppressed LPS-mediated iNOS/COX-2 expression by western blot, RT-PCR, reporter gene assay and confocal microscope analysis.</p> <p>Results</p> <p>Aciculatin remarkably decreased the LPS (1 μg/mL)-induced mRNA and protein expression of iNOS and COX-2 as well as their downstream products, NO and PGE<sub>2 </sub>respectively, in a concentration-dependent manner (1-10 μM). Such inhibition was found, via immunoblot analyses, reporter gene assays, and confocal microscope observations that aciculatin not only acts through significant suppression of LPS-induced NF-κB activation, an effect highly correlated with its inhibitory effect on LPS-induced IκB kinase (IKK) activation, IκB degradation, NF-κB phosphorylation, nuclear translocation and binding of NF-κB to the κB motif of the iNOS and COX-2 promoters, but also suppressed phosphorylation of JNK/p38 mitogen-activated protein kinases (MAPKs).</p> <p>Conclusion</p> <p>Our results demonstrated that aciculatin exerts potent anti-inflammatory activity through its dual inhibitory effects on iNOS and COX-2 by regulating NF-κB and JNK/p38 MAPK pathways.</p
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