227 research outputs found

    A study on dynamical complexity of noise induced blood flow

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    In this article, the dynamics and complexity of a noise induced blood flow system have been investigated. Changes in the dynamics have been recognized by measuring the periodicity over significant parameters. Chaotic as well as non-chaotic regimes have also been classified. Further, dynamical complexity has been studied by phase space based weighted entropy. Numerical results show a strong correlation between the dynamics and complexity of the noise induced system. The correlation has been confirmed by a cross-correlation analysis

    Non-integrability of dominated splitting on T2\mathbb{T}^2

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    We construct a diffeomorphism ff on 2-torus with a dominated splitting E⊕FE \oplus F such that there exists an open neighborhood U∋f\mathcal{U} \ni f satisfying that for any g∈Ug \in \mathcal{U}, neither EgE_g nor FgF_g is integrable

    Separation and purification of the bovine milk fat globule membrane protein and its effect on improvement of C2C12 mouse skeletal muscle cell proliferation

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    A novel method to improve the proliferation activity of C2C12 cells by the bovine milk fat globule membrane (MFGM) protein was established in this study. The MFGM protein was extracted and isolated into 4 fractions using an electric cream separator, and purified by a cellulose DEAE-52 column. Fraction 2 accounted for 57.8% of the total MFGM protein, and was used in the following study. The MTT assay showed that it induced cell proliferation activity, increased the cell survival rate and the cell number using flow cytometry and fluorescence microscopy analysis. There were only subtle changes in the morphology as observed using confocal scanning laser microscopy, but the number of mitochondria was significantly increased as observed using transmission electron microscopy analysis. Furthermore, the mRNA expression of MyoD, cyclin D1, p70S6K and mTOR was up-regulated as determined utilizing the quantitative real-time PCR assay, and the activation of Akt and mTOR phosphorylation was up regulated as determined using the Western blot assay. The main protein in fraction 2, assayed by 1-D gel electrophoresis and MALDI TOF-TOF, was identified as milk fat globule-EGF factor 8, the content was 65.6% of the total protein in fraction 2. The results elucidate a new molecular mechanism of the MFGM protein fraction 2: the activation of the Akt signal pathway in promoting cell proliferation

    MFG-E8 induced differences in proteomic profiles in mouse C2C12 cells and its effect on PI3K/Akt and ERK signal pathways

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    Milk fat globule-EGF factor 8 (MFG-E8) is one of the major proteins in milk fat globule membrane. In this study, mouse-derived C2C12 myoblast cells were served as an experimentally tractable model system for investigating the molecular basis of skeletal muscle cell specification and development. To examine the biochemical adaptations associated with myocytes formation comprehensively, a liquid chromatography coupled with tandem mass spectrometry label-free semi-quantitative  approach was used to analyse the myogenic C2C12 proliferation program. Over 1987  proteins were identified in C2C12 cells. The MFG-E8 (200 mg/mL) and MFG-E8 (500 26 mg/mL) with significant differences were compared based on the relative abundance. The result profiles of regulation of MFG-E8 to the expression of proteins in C2C12 cells revealed that differential waves of expression of proteins linked to intracellular signaling, transcription, cytoarchitecture, adhesion, metabolism, and muscle contraction across during the C2C12 cell proliferation process. Based on the analysis of  KEGG and STRING database, further to verification the expression of PI3K and ERK phosphorylation levels by Western blot. This study found that the data of proteomic was complementary to recent MFG-E8 studies of protein expression patterns in developing myotubes and provided a holistic framework for understanding how diverse biochemical processes are coordinated at the cellular level during skeletal muscle development

    Milk fat globule membrane protein promotes C2C12 cell proliferation through the PI3K/Akt signaling pathway

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    Milk fat globule membrane (MFGM) protein is known to have several health benefits, including an anti-sarcopenia effect; however, its mechanism is unclear. The aim of this study was to investigate the potential mechanism of action of the MFGM protein. The MFGM protein was extracted and separated into 4 fractions, and Fraction 2 (57 % of total MFGM) demonstrated the greatest effect on C2C12 cell proliferation. Milk fat globule-EGF factor 8 (MFG-E8) accounted for 82.35 % of the MFGM protein. The effects of whole Fraction 2 (100 μg/mL, 200 μg/mL and 300 μg/mL) on cell proliferation and morphology were measured. Using qRT-PCR or a Western blot assay, several regulatory factors, e.g., PI3K P85α, p-pI3K p85α (Tyr 508), Akt, p-Akt (Ser 473), mTOR and p-mTOR (Ser 2448), were measured in cells incubated with 200 μg/mL of Fraction 2 with or without wortmannin. The results demonstrated that Fraction 2 induced C2C12 cell proliferation in a dose-dependent manner, upregulated the mRNA expression of mTOR and p70S6K, and activated PI3K, Akt, mTOR and P70S6K phosphorylation; however, Fraction 2 inhibited FOXO3a and 4E-BP. The results demonstrate that the MFGM protein, predominantly MFG-E8, promotes cell proliferation through the PI3K/Akt/mTOR signaling pathway. This study elucidated the molecular mechanism of the MFGM protein, primarily MFG-E8, in promoting C2C12 cell proliferation via the PI3K/Akt/mTOR/P70S6K signal pathway

    Gamma-tocotrienol stimulates the proliferation, differentiation, and mineralization in osteoblastic MC3T3-E1 cells

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    Gamma-tocotrienol, a major component of tocotrienol-rich fraction of palm oil, has been suggested to exhibit bone protective effects in vivo. However, the effects of γ-tocotrienol on osteoblast cells are still unclear. In this study, the effects of γ-tocotrienol on the proliferation, differentiation, and mineralization in osteoblastic MC3T3-E1 cells were investigated. Our results showed that γ-tocotrienol (2–8 μmol/L) significantly improved the cell proliferation (), but it did not affect cell cycle progression. γ-Tocotrienol significantly increased alkaline phosphatase (ALP) activity (), secretion levels of osteocalcin (OC) and osteonectin (ON), and mRNA levels of collagen type I (Col I) of MC3T3-E1 cells. Meanwhile, we found that γ-tocotrienol is promoted in differentiation MC3T3-E1 cells by upregulation of the expression of Runx2 protein. Moreover, the number of bone nodules increased over 2.5-fold in cells treated with γ-tocotrienol (2–8 μmol/L) for 24 d compared to control group. These results indicated that γ-tocotrienol at low dose levels, especially 4 μmol/L, could markedly enhance the osteoblastic function by increasing the proliferation, differentiation, and mineralization of osteoblastic MC3T3-E1 cells. Moreover, our data also indicated that Runx2 protein may be involved in these effects. Further studies are needed to determine the potential of γ-tocotrienol as an antiosteoporotic agent

    Bipartite Graph Pre-training for Unsupervised Extractive Summarization with Graph Convolutional Auto-Encoders

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    Pre-trained sentence representations are crucial for identifying significant sentences in unsupervised document extractive summarization. However, the traditional two-step paradigm of pre-training and sentence-ranking, creates a gap due to differing optimization objectives. To address this issue, we argue that utilizing pre-trained embeddings derived from a process specifically designed to optimize cohensive and distinctive sentence representations helps rank significant sentences. To do so, we propose a novel graph pre-training auto-encoder to obtain sentence embeddings by explicitly modelling intra-sentential distinctive features and inter-sentential cohesive features through sentence-word bipartite graphs. These pre-trained sentence representations are then utilized in a graph-based ranking algorithm for unsupervised summarization. Our method produces predominant performance for unsupervised summarization frameworks by providing summary-worthy sentence representations. It surpasses heavy BERT- or RoBERTa-based sentence representations in downstream tasks.Comment: Accepted by the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023
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