562 research outputs found

    The ciliary GTPase Arl13b regulates cell migration and cell cycle progression

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    Acknowledgments We acknowledge Prof. Tamara Caspary from Emory University for kindly providing the cell lines, Linda Duncan from the University of Aberdeen Ian Fraser Cytometry Center for help with flow cytometry. MP was funded by the Scottish Universities Life Science Alliance (SULSA) and the University of Aberdeen. Funding This work was supported by grants from British Council China (Sino-UK higher Education for PhD studies) to YD and CM, The Carnegie Trust for the Universities of Scotland (70190) and The NHS Grampian Endowment Funds (14/09) to BL, and National Natural Science Foundation of China (31528011) to BL and YD.Peer reviewedPostprin

    A zinc finger protein Zfp521 directs neural differentiation and beyond

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    Neural induction is largely considered a default process, whereas little is known about intrinsic factors that drive neural differentiation. Kamiya and colleagues now demonstrate that a transcription factor, Zfp521, is capable of directing embryonic stem (ES) cells into neural progenitors. They discovered that Zfp521 transcripts were enriched in early neural lineage of ES cell differentiation. Forced expression of Zfp521 turned ES cells into neural progenitors in culture conditions that would normally inhibit neural differentiation. Zfp521 was expressed in mouse embryos during gastrulation. The protein was shown to associate with a co-activator p300 and directly induce expression of early neural genes. Knockdown of the Zfp521 by shRNA halted cells at the epiblast stage and suppressed neural differentiation. Zfp521 is a nuclear protein with 30 Krüppel-like zinc fingers mediating multiple protein-protein interactions, and regulates transcription in diverse tissues and organs. The protein promotes proliferation, delays differentiation and reduces apoptosis. The findings by Kamiya and colleagues that Zfp521 directs and sustains early neural differentiation now opens up a series of studies to investigate roles of Zfp521 in stem cells and brain development of mice and men

    Neurochemical characterization of pERK-expressing spinal neurons in histamine-induced itch

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    Date of Acceptance: 08/07/2015 Acknowledgements This work was supported by grants from the Ministry of Science and Technology of China (2012CB966904, 2011CB51005), National Natural Science Foundation of China (31271182, 81200692, 91232724, 81200933, 81101026), Shanghai Natural Science Foundation (12ZR1434300), Key Specialty Construction Project of Pudong Health Bureau of Shanghai (PWZz2013-17), Shenzhen Key Laboratory for Molecular Biology of Neural Development (ZDSY20120617112838879), Fundamental Research Funds for the Central Universities (1500219072) and Sino-UK Higher Education Research Partnership for PhD Studies.Peer reviewedPublisher PD

    Oxytocin is implicated in social memory deficits induced by early sensory deprivation in mice

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    Acknowledgements We thank Miss Jia-Yin and Miss Yu-Ling Sun for their help in breading the mice. Funding This work was supported by grants from the National Natural Science Foundation of China (81200933 to N.-N. Song; 81200692 to L. Chen; 81101026 to Y. Huang; 31528011 to B. Lang; 81221001, 91232724 and 81571332 to Y-Q. Ding), Zhejiang Province Natural Science Foundation of China (LQ13C090004 to C. Zhang), China Postdoctoral Science Foundation (2016 M591714 to C.-C. Qi), and the Fundamental Research Funds for the Central Universities (2013KJ049).Peer reviewedPublisher PD

    Domestic water demand forecasting in the Yellow River basin under changing environment

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    Purpose: The purpose of this paper is to develop a statistical-based model to forecast future domestic water demand in the context of climate change, population growth and technological development in Yellow River. Design/methodology/approach: The model is developed through the analysis of the effects of climate variables and population on domestic water use in eight sub-basins of the Yellow River. The model is then used to forecast water demand under different environment change scenarios. Findings: The model projected an increase in domestic water demand in the Yellow River basin in the range of 67.85 × 108 to 62.20 × 108 m3 in year 2020 and between 73.32 × 108 and 89.27 × 108 m3 in year 2030. The general circulation model Beijing Normal University-Earth System Model (BNU-ESM) predicted the highest increase in water demand in both 2020 and 2030, while Centre National de Recherches Meteorologiques Climate Model v.5 (CNRM-CM5) and Model for Interdisciplinary Research on Climate- Earth System (MIROC-ESM) projected the lowest increase in demand in 2020 and 2030, respectively. The fastest growth in water demand is found in the region where water demand is already very high, which may cause serious water shortage and conflicts among water users. Originality/value: The simple regression-based domestic water demand model proposed in the study can be used for rapid evaluation of possible changes in domestic water demand due to environmental changes to aid in adaptation and mitigation planning

    The Ras Superfamily of Small GTPases in Non-neoplastic Cerebral Diseases

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    The small GTPases from the Ras superfamily play crucial roles in basic cellular processes during practically the entire process of neurodevelopment, including neurogenesis, differentiation, gene expression, membrane and protein traffic, vesicular trafficking, and synaptic plasticity. Small GTPases are key signal transducing enzymes that link extracellular cues to the neuronal responses required for the construction of neuronal networks, as well as for synaptic function and plasticity. Different subfamilies of small GTPases have been linked to a number of non-neoplastic cerebral diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), intellectual disability, epilepsy, drug addiction, Huntington’s disease (HD), amyotrophic lateral sclerosis (ALS) and a large number of idiopathic cerebral diseases. Here, we attempted to make a clearer illustration of the relationship between Ras superfamily GTPases and non-neoplastic cerebral diseases, as well as their roles in the neural system. In future studies, potential treatments for non-neoplastic cerebral diseases which are based on small GTPase related signaling pathways should be explored further. In this paper, we review all the available literature in support of this possibility

    First-phase ejection fraction by CMR predicts outcomes in aortic stenosis

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    BACKGROUND: First-phase ejection fraction (EF1; the ejection fraction measured during active systole up to the time of maximal aortic flow) measured by transthoracic echocardiography (TTE) is a powerful predictor of outcomes in patients with aortic stenosis. We aimed to assess whether cardiovascular magnetic resonance (CMR) might provide more precise measurements of EF1 than TTE and to examine the correlation of CMR EF1 with measures of fibrosis. METHODS: In 141 patients with at least mild aortic stenosis, we measured CMR EF1 from a short-axis 3D stack and compared its variability with TTE EF1, and its associations with myocardial fibrosis and clinical outcome (aortic valve replacement (AVR) or death). RESULTS: Intra- and inter-observer variation of CMR EF1 (standard deviations of differences within and between observers of 2.3% and 2.5% units respectively) was approximately 50% that of TTE EF1. CMR EF1 was strongly predictive of AVR or death. On multivariable Cox proportional hazards analysis, the hazard ratio for CMR EF1 was 0.93 (95% confidence interval 0.89–0.97, p = 0.001) per % change in EF1 and, apart from aortic valve gradient, CMR EF1 was the only imaging or biochemical measure independently predictive of outcome. Indexed extracellular volume was associated with AVR or death, but not after adjusting for EF1. CONCLUSIONS: EF1 is a simple robust marker of early left ventricular impairment that can be precisely measured by CMR and predicts outcome in aortic stenosis. Its measurement by CMR is more reproducible than that by TTE and may facilitate left ventricular structure–function analysis
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