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[en] To develop a method of analyzing apoptosis using multi-parameter flow cytometry, HL60 cell line was incubated with Annexin V-FITC/PI after exposure to etoposide, and the apoptosis of HL60 cell was monitored by flow cytometry. The result showed that the percentage of apoptosis cell increases with the time of exposure to etoposide. In conclusion, Annexin V FITC/PI method can not only detect special proteins, but also monitor the integrity of cell membrane. Multi-parameter flow cytometry is a rapid, easy and accurate method for the detection of apoptosis
[en] Graphical abstract: Hybrid nanofillers of the CNTs and AgNPs were embedded into a shape memory polyurethane. The composites exhibited tunable conduction, which could be facially tailored by the compositions and the thermal–mechanical programming. - Highlights: • Electrically conductive polymer composites in bi-layer structure were fabricated. • The CNTs/AgNPs layer had influence on the mechanics and thermal transitions. • The conductivity could be facially tailored via a thermo-mechanical programming. • The AgNPs contents enlarged the gauge factor of the resistivity–strain curves. • Tunneling theory was suitable for simulating the strain-dependent behaviors. - Abstract: A conductive composite in bi-layer structure was fabricated by embedding hybrid nanofillers, namely carbon nanotubes (CNTs) and silver nanoparticles (AgNPs), into a shape memory polyurethane (SMPU). The CNT/AgNP-SMPU composites exhibited a novel tunable conductivity which could be facially tailored in wide range via the compositions or a specifically designed thermo-mechanical shape memory programming. The morphologies of the conductive fillers and the composites were investigated by scanning electron microscope (SEM). The mechanical and thermal measurements were performed by tensile tests and differential scanning calorimetry (DSC). By virtue of a specifically explored shape memory programming, the composites were stretched and fixed into different temporary states. The electrical resistivity (R_s) varied accordingly, which was able to be stabilized along with the shape fixing. Theoretical prediction based upon the tunneling model was performed. The R_s–strain curves of the composites with different compositions were well fitted. Furthermore, the relative resistivity and the Gauge factor along with the elongation were calculated. The influence of the compositions on the strain-dependent R_s was disclosed. The findings provided a new avenue to tailor the conductivity of the polymeric nano-composites by combining the composition method and a thermo-mechanical programming, which may greatly benefit the application of intelligent polymers in flexible electronics and sensors fields.