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Tiefang Guo

Publications and source records attributed to Tiefang Guo.

3 recordsLinked to original sources

Tissue-engineered vessel strengthens quickly under physiological deformation: application of a new perfusion bioreactor with machine vision.

In order to develop a patent tissue-engineered blood vessel that grossly resembles native tissue, required culture times in most studies exceed 8 weeks. For the sake of shortening the maturation period of the constructs, we have used deformation as the basic index for mechanical environment control. A new bioreactor with a machine vision identifier was developed to accurately control the deformation of the construct during the perfusion process. Two groups of seeded constructs (n = 4 per group) were investigated in this study, with one group stimulated by a cyclic deformation of 10% and the other by a pulsatile pressure that gradually increased to 120 mm Hg (the control group). After 21 days of culture, the mechanical properties of the constructs were examined. The average burst strength and suture retention strength in the two groups were significantly different (t test, p < 0.05). For the experimental group, the average burst strength and suture retention strength were higher than those of the control group, by 31.6 and 23.4%, respectively. Specifically, the average burst strength of the constructs reached 1,402 mm Hg (close to that of the native vessel, i.e. 1,680 mm Hg) within a relatively short period of 21 days. In conclusion, deformation is an observable, controllable and very valuable index for mechanical environment control in vascular tissue engineering. It makes the control of mechanical stimuli more essential and experiments more comparable.

Animals↗

Applying informatics in tissue engineering.

OBJECTIVE: To facilitate tissue engineering strategies determination with informatics tools. METHODS: Firstly, tissue engineering experimental data were standardized and integrated into a centralized database; secondly, we used data mining tools (e.g. artificial neural networks and decision trees) to predict the outcomes of tissue engineering strategies; thirdly, a strategy design algorithm was developed, and its efficacy was validated with animal experiments; lastly, we constructed an online database and a decision support system for tissue engineering. RESULTS: The artificial neural networks and the decision trees respectively predicted the outcomes of tissue engineering strategies with the predictive accuracy of 95.14% and 85.26%. Following the strategies generated by computer, we cured 18 of the 20 experimental animals with a significantly lower cost than usual. CONCLUSION: Informatics is beneficial for realizing safe, effective and economical tissue engineering.

Artificial Intelligence↗

[Effect of triton X-100 on preparing porcine thoracic aortas acellular matrix].

OBJECTIVES: To investigate the method of preparing porcine thoracic aortas acellular tissue matrix (ACTM) by trypsin, EDTA and Triton X-100 and to find the best concentration of X-100. METHODS: A total of 56 roots of fresh thoracic aortas (without adventitial tissue) from 80 kg-100 kg tame pigs were divided randomly into > groups, each containing 8 roots. Every vessel was put into a 50 ml centrifugal tube with a solution of 0.1% trypsin + 0.02EDTA in PBS for 24 h. After that, each group was separately immerged into a solution of 0.1%, 0.2%, 0.5%, 1.0%, 2.0%, 5.0%, 10.0% Triton X-100 for 144 h-240 h. Specimens were taken every 6 h. Specimens were stained with haematoxylin-eosin and observed grossly under the light and transmission electron microscopy. RESULTS: Light and transmission electron microscopy revealed that ACTM was composed of insoluble collagen, elastin, and some insoluble metamorphic organelles. The best concentration of Triton X-100 was 1% at the time of 176.25 h +/- 5.5 h. CONCLUSIONS: Porcine thoracic aortas ACTM can be obtained successfully through this procedure. Triton X-100 is a good reagent for preparing vessel ACTM.

Animals↗