Biomedical subjects

Haiyan Ge

Publications and source records attributed to Haiyan Ge.

4 recordsLinked to original sources

PubMed2005

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↗

PubMed2005

Prediction of vascular tissue engineering results with artificial neural networks.

Tissue engineers are often confused on finding the most successful strategy for specific patient. In this study, we used artificial neural networks to predict the outcomes of different vascular tissue engineering strategies, thus providing advisory information for experimental designers. Over 30 variables were used as features of the tissue engineering strategies. Different architectures of artificial neural networks with back propagation algorithm were tested to obtain the best model configuration for the prediction of the tissue engineering strategies. In the computational experiments, the artificial neural networks with one and two hidden layers could, respectively, detect unsuccessful strategies with the highest predictive accuracy of 91.45 and 94.24%. In conclusion, artificial intelligence has great potential in tissue engineering decision support. It can provide accurate advisory information for tissue engineers, thus reducing failures and improving therapeutic effects.

Animals↗

PubMed2005

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↗

PubMed2003

Kakadumycins, novel antibiotics from Streptomyces sp NRRL 30566, an endophyte of Grevillea pteridifolia.

An endophytic streptomycete (NRRL 30566) is described and partially characterized from a fern-leaved grevillea (Grevillea pteridifolia) tree growing in the Northern Territory of Australia. This endophytic streptomycete produces, in culture, novel antibiotics - the kakadumycins. Methods are outlined for the production and chemical characterization of kakadumycin A and related compounds. This antibiotic is structurally related to a quinoxaline antibiotic, echinomycin. Each contains, by virtue of their amino acid compositions, alanine, serine and an unknown amino acid. Other biological, spectral and chromatographic differences between these two compounds occur and are given. Kakadumycin A has wide spectrum antibiotic activity, especially against Gram-positive bacteria, and it generally displays better bioactivity than echinomycin. For instance, against Bacillus anthracis strains, kakadumycin A has minimum inhibitory concentrations of 0.2-0.3 microg x ml(-1) in contrast to echinomycin at 1.0-1.2 microg x ml(-1). Both echinomycin and kakadumycin A have impressive activity against the malarial parasite Plasmodium falciparum with LD(50)s in the range of 7-10 ng x ml(-1). In macromolecular synthesis assays both kakadumycin A and echinomycin have similar effects on the inhibition of RNA synthesis. It appears that the endophytic Streptomyces sp. offer some promise for the discovery of novel antibiotics with pharmacological potential.

Anti-Bacterial Agents↗