Objective To establish a method for quantitative detection of the sulfate glycosaminoglycans ( GAG) content in extracellular matrix of in vitro cultured chondrocytes so as to evaluate the biological characteristics of...Objective To establish a method for quantitative detection of the sulfate glycosaminoglycans ( GAG) content in extracellular matrix of in vitro cultured chondrocytes so as to evaluate the biological characteristics of epiphyseal, articular and rib chondrocytes. Methods Sulfate GAG content in extracellular matrix of three chondrocytes was measured by the modified dimethylmethylene blue (DMB) method. The changes of the toluidine blue (TB) stain of chondrocytes were observed by light microscope. Results Primary chondrocytes had the highest content of sulfate GAG in the extracellular matrix, ie, epiphyseal chondrocytes reached ( 70. 12 ± 7. 72 )μg/cm2, articular chondrocytes (92.00 ± 10.15) μg/cm2 and rib chondrocytes (80.61 ± 11. 40) μg/cm2, respectively. On the third pasage chondrocytes, epiphyceal chondrocytes decreased to (53.27 ± 9. 50 ) μg/cm2, articular chondrocytes to (63.88 ± 11.92) μg/cm2 and rib chondrocytes to (58.94 ±8.21) μg/cm2, respectively. The change of TB in every passage展开更多
The mechanical properties of materials greatly depend on the microstructure morphology. The quantitative characterization of material microstructures is essential for the performance prediction and hence the material ...The mechanical properties of materials greatly depend on the microstructure morphology. The quantitative characterization of material microstructures is essential for the performance prediction and hence the material design. At present,the quantitative characterization methods mainly rely on the microstructure characterization of shape, size, distribution,and volume fraction, which related to the mechanical properties. These traditional methods have been applied for several decades and the subjectivity of human factors induces unavoidable errors. In this paper, we try to bypass the traditional operations and identify the relationship between the microstructures and the material properties by the texture of image itself directly. The statistical approach is based on gray level Co-occurrence matrix(GLCM), allowing an objective and repeatable study on material microstructures. We first present how to identify GLCM with the optimal parameters, and then apply the method on three systems with different microstructures. The results show that GLCM can reveal the interface information and microstructures complexity with less human impact. Naturally, there is a good correlation between GLCM and the mechanical properties.展开更多
文摘Objective To establish a method for quantitative detection of the sulfate glycosaminoglycans ( GAG) content in extracellular matrix of in vitro cultured chondrocytes so as to evaluate the biological characteristics of epiphyseal, articular and rib chondrocytes. Methods Sulfate GAG content in extracellular matrix of three chondrocytes was measured by the modified dimethylmethylene blue (DMB) method. The changes of the toluidine blue (TB) stain of chondrocytes were observed by light microscope. Results Primary chondrocytes had the highest content of sulfate GAG in the extracellular matrix, ie, epiphyseal chondrocytes reached ( 70. 12 ± 7. 72 )μg/cm2, articular chondrocytes (92.00 ± 10.15) μg/cm2 and rib chondrocytes (80.61 ± 11. 40) μg/cm2, respectively. On the third pasage chondrocytes, epiphyceal chondrocytes decreased to (53.27 ± 9. 50 ) μg/cm2, articular chondrocytes to (63.88 ± 11.92) μg/cm2 and rib chondrocytes to (58.94 ±8.21) μg/cm2, respectively. The change of TB in every passage
基金Project supported by the National Natural Science Foundation of China(Grant Nos.5147113 and 51505037)the Fundamental Research Funds for the Central Universities of Ministry of Education of China(Grant Nos.3102017zy029,310832163402,and 310832163403)
文摘The mechanical properties of materials greatly depend on the microstructure morphology. The quantitative characterization of material microstructures is essential for the performance prediction and hence the material design. At present,the quantitative characterization methods mainly rely on the microstructure characterization of shape, size, distribution,and volume fraction, which related to the mechanical properties. These traditional methods have been applied for several decades and the subjectivity of human factors induces unavoidable errors. In this paper, we try to bypass the traditional operations and identify the relationship between the microstructures and the material properties by the texture of image itself directly. The statistical approach is based on gray level Co-occurrence matrix(GLCM), allowing an objective and repeatable study on material microstructures. We first present how to identify GLCM with the optimal parameters, and then apply the method on three systems with different microstructures. The results show that GLCM can reveal the interface information and microstructures complexity with less human impact. Naturally, there is a good correlation between GLCM and the mechanical properties.