AIM: To facilitate close contacts between transplanted cardiomyocytes and host skeletal muscle using cell fusion mediated by hemagglutinating virus of Japan envelope(HVJ-E) and tissue maceration. METHODS: Cardiomyocyt...AIM: To facilitate close contacts between transplanted cardiomyocytes and host skeletal muscle using cell fusion mediated by hemagglutinating virus of Japan envelope(HVJ-E) and tissue maceration. METHODS: Cardiomyocytes(1.5 × 106) from fetal rats were first cultured. After proliferation, some cells were used for fusion with adult muscle fibers using HVJ-E. Other cells were used to create cardiomyocyte sheets(area: about 3.5 cm2 including 2.1 × 106 cells), which were then treated with Nile blue, separated, and transplanted between the latissimus dorsi and intercostal muscles of adult rats with four combinations of HVJ-E and/or Na OH maceration: G1: HVJ-E(+), Na OH(+), Cardiomyocytes(+); G2: HVJ-E(-), NaO H(+), Cardiomyocytes(+); G3: HVJ-E(+),Na OH(-), Cardiomyocytes(+); G4: HVJ-E(-), Na OH(-), Cardiomyocytes(-). At 1 and 2 wk after transplantation, the four groups were compared by detection of beating domains, motion images using moving target analysis software, action potentials, gene expression of MLC-2v and Mesp1 by reverse transcription-polymerase chain reaction, hematoxylin-eosin staining, and immunostaining for cardiac troponin and skeletal myosin.RESULTS: In vitro cardiomyocytes were fused with skeletal muscle fibers using HVJ-E. Cardiomyocyte sheets remained in the primary transplanted sites for 2 wk. Although beating domains were detected in G1, G2, and G3 rats, G1 rats prevailed in the number, size, motion image amplitudes, and action potential compared with G2 and G3 rats. Close contacts were only found in G1 rats. At 1 wk after transplantation, the cardiomyocyte sheets showed adhesion at various points to the myoblast layer in the latissimus dorsi muscle. At 2 wk after transplantation, close contacts were seen over a broad area. Part of the skeletal muscle sarcoplasma seemed to project into the myocardiocyte plasma and some nuclei appeared to share both sarcoplasmas.CONCLUSION: The present results show that close contacts were acquired and facilitated the beating function, thereby providing a new cellular transplantation method using HVJ-E and NaO H maceration.展开更多
The classic data envelopment analysis（DEA） model is used to evaluate decision-making units＇（DMUs） efficiency under the assumption that all DMUs are evaluated with the same criteria setting. Recently, new research...The classic data envelopment analysis（DEA） model is used to evaluate decision-making units＇（DMUs） efficiency under the assumption that all DMUs are evaluated with the same criteria setting. Recently, new researches begin to focus on the efficiency analysis of non-homogeneous DMU arose by real practices such as the evaluation of departments in a university, where departments argue for the adoption of different criteria based on their disciplinary characteristics. A DEA procedure is proposed in this paper to address the efficiency analysis of two non-homogeneous DMU groups. Firstly, an analytical framework is established to compromise diversified input and output（IO） criteria from two nonhomogenous groups. Then, a criteria fusion operation is designed to obtain different DEA analysis strategies. Meanwhile, Friedman test is introduced to analyze the consistency of all efficiency results produced by different strategies. Next, ordered weighted averaging（OWA） operators are applied to integrate different information to reach final conclusions. Finally, a numerical example is used to illustrate the proposed method. The result indicates that the proposed method relaxes the restriction of the classical DEA model,and can provide more analytical flexibility to address different decision analysis scenarios arose from practical applications.展开更多
Bearing fault diagnosis is vital to safeguard the heath of rotating machinery.It can help to avoid economic losses and safe accidents in time.Effective feature extraction is the premise of diagnosing bearing faults.Ho...Bearing fault diagnosis is vital to safeguard the heath of rotating machinery.It can help to avoid economic losses and safe accidents in time.Effective feature extraction is the premise of diagnosing bearing faults.However,effective features characterizing the health status of bearings are difficult to extract from the raw bearing vibration signals.Furthermore,inefficient feature extraction results in substantial time wastage,making it hard to apply in realtime monitoring.A novel feature extraction method for diagnosing bearing faults using multiscale improved envelope spectrum entropy(MIESE)is proposed in this work.First,bearing vibration signals are analyzed across multiple scales,and improved envelope spectrum entropy(IESE)is extracted fromthese signals at each scale to form an original feature set.Subsequently,joint approximate diagonalization eigenmatrices(JADE)is applied to fuse above feature set for effectively eliminating redundancy and generated a refined feature set.Finally,the newly generated feature set is input into support vectormachines(SVMs)to effectively diagnose bearing health status.Two cases studies are employed to demonstrate the reliability of the proposed method.The results illustrate that the proposed method can improve the stability of extracted features and increase the computational efficiency.展开更多
基金Supported by A Grant-in-Aid for Scientific Research from the Japanese Ministry of Education,Science and Sports,No.24240076
文摘AIM: To facilitate close contacts between transplanted cardiomyocytes and host skeletal muscle using cell fusion mediated by hemagglutinating virus of Japan envelope(HVJ-E) and tissue maceration. METHODS: Cardiomyocytes(1.5 × 106) from fetal rats were first cultured. After proliferation, some cells were used for fusion with adult muscle fibers using HVJ-E. Other cells were used to create cardiomyocyte sheets(area: about 3.5 cm2 including 2.1 × 106 cells), which were then treated with Nile blue, separated, and transplanted between the latissimus dorsi and intercostal muscles of adult rats with four combinations of HVJ-E and/or Na OH maceration: G1: HVJ-E(+), Na OH(+), Cardiomyocytes(+); G2: HVJ-E(-), NaO H(+), Cardiomyocytes(+); G3: HVJ-E(+),Na OH(-), Cardiomyocytes(+); G4: HVJ-E(-), Na OH(-), Cardiomyocytes(-). At 1 and 2 wk after transplantation, the four groups were compared by detection of beating domains, motion images using moving target analysis software, action potentials, gene expression of MLC-2v and Mesp1 by reverse transcription-polymerase chain reaction, hematoxylin-eosin staining, and immunostaining for cardiac troponin and skeletal myosin.RESULTS: In vitro cardiomyocytes were fused with skeletal muscle fibers using HVJ-E. Cardiomyocyte sheets remained in the primary transplanted sites for 2 wk. Although beating domains were detected in G1, G2, and G3 rats, G1 rats prevailed in the number, size, motion image amplitudes, and action potential compared with G2 and G3 rats. Close contacts were only found in G1 rats. At 1 wk after transplantation, the cardiomyocyte sheets showed adhesion at various points to the myoblast layer in the latissimus dorsi muscle. At 2 wk after transplantation, close contacts were seen over a broad area. Part of the skeletal muscle sarcoplasma seemed to project into the myocardiocyte plasma and some nuclei appeared to share both sarcoplasmas.CONCLUSION: The present results show that close contacts were acquired and facilitated the beating function, thereby providing a new cellular transplantation method using HVJ-E and NaO H maceration.
基金supported by the National Natural Science Foundation of China(71471087)
文摘The classic data envelopment analysis（DEA） model is used to evaluate decision-making units＇（DMUs） efficiency under the assumption that all DMUs are evaluated with the same criteria setting. Recently, new researches begin to focus on the efficiency analysis of non-homogeneous DMU arose by real practices such as the evaluation of departments in a university, where departments argue for the adoption of different criteria based on their disciplinary characteristics. A DEA procedure is proposed in this paper to address the efficiency analysis of two non-homogeneous DMU groups. Firstly, an analytical framework is established to compromise diversified input and output（IO） criteria from two nonhomogenous groups. Then, a criteria fusion operation is designed to obtain different DEA analysis strategies. Meanwhile, Friedman test is introduced to analyze the consistency of all efficiency results produced by different strategies. Next, ordered weighted averaging（OWA） operators are applied to integrate different information to reach final conclusions. Finally, a numerical example is used to illustrate the proposed method. The result indicates that the proposed method relaxes the restriction of the classical DEA model,and can provide more analytical flexibility to address different decision analysis scenarios arose from practical applications.
基金supported in part by the Key Basic Research Project MKF20210008.
文摘Bearing fault diagnosis is vital to safeguard the heath of rotating machinery.It can help to avoid economic losses and safe accidents in time.Effective feature extraction is the premise of diagnosing bearing faults.However,effective features characterizing the health status of bearings are difficult to extract from the raw bearing vibration signals.Furthermore,inefficient feature extraction results in substantial time wastage,making it hard to apply in realtime monitoring.A novel feature extraction method for diagnosing bearing faults using multiscale improved envelope spectrum entropy(MIESE)is proposed in this work.First,bearing vibration signals are analyzed across multiple scales,and improved envelope spectrum entropy(IESE)is extracted fromthese signals at each scale to form an original feature set.Subsequently,joint approximate diagonalization eigenmatrices(JADE)is applied to fuse above feature set for effectively eliminating redundancy and generated a refined feature set.Finally,the newly generated feature set is input into support vectormachines(SVMs)to effectively diagnose bearing health status.Two cases studies are employed to demonstrate the reliability of the proposed method.The results illustrate that the proposed method can improve the stability of extracted features and increase the computational efficiency.
