The authors aim to track the distribution of human umbilical cord mesenchymal stem cells (MSCs) in large blood vessel of traumatic brain injury -rats through immunohistochemical method and small animal imaging system. After green fluorescent protein (GFP) gene was transfected into 293T cell, virus was packaged and MSCs were transfected. Mesenchymal stem cells containing GFP were transplanted into brain ventricle of rats when the infection rate reaches 95%. The immunohistochemical and small animal imaging system was used to detect the distribution of MSCs in large blood vessels of rats. Mesenchymal stem cells could be observed in large vessels with positive GFP expression 10 days after transplantation, while control groups (normal group and traumatic brain injury group) have negative GFP expression. The vascular endothelial growth factor in transplantation group was higher than that in control groups. The in vivo imaging showed obvious distribution of MSCs in the blood vessels of rats, while no MSCs could be seen in control groups. The intravascular migration and homing of MSCs could be seen in rats received MSCs transplantation, and new angiogenesis could be seen in MSCs-transplanted blood vessels.
Alcohol content is an important indicator of many products, rapid and accurate analysis is the key link of commodity inspection and productive process. Study using NIRS model to detect alcohol content of wine, adopted genetic algorithm partial least-squares (GA-PLS) method to analyze the near-infrared spectroscopy (NIRS) characteristic wavelengths of alcohol content, the best NIR GA-PLS model is established. Experiment find GA-PLS can flexible and effective select out the characteristic wavelengths, can not only get rid of the useless information wavelengths, but also improve model’s predicted precision, therefore, the predicted precision of GA-PLS model superior to PLS model established with global spectrum. The best predicted effect is obtained when 133 wavelengths with higher selected frequency join modeling, its root mean square error of prediction (RMSEP) is 0.0066 and correlation coefficient of prediction (R P ) is 0.9996. The results show, NIRS combined with GA-PLS method can detect alcohol content of wine rapidly and accurately, expected to achieve rapid detection of alcohol content online.
To improve the signal-to-noise ratio (SNR) of the dynamic spectrum (DS) data and to increase the stability of the model and the prediction accuracy, the harmonic waves of DS data were introduced into DS method. Sixty samples were determined as the research objects according to the quality of the pulse wave and the distribution of the harmonic waves after further analysis of 110 volunteers' data acquired in vivo. This paper took whether adding the energy of harmonic waves into the DS data as the division standard to generate two groups. BP artificial neural network was used to establish the calibration model of subjects' hemoglobin values against DS. The correlation coefficients of the predicted values and the true values in experimental group, containing the energy of harmonic waves, was 0.91, much higher than 0.80 in the control group. Other indexes were all improved too. The results showed that the modified method can enhance the SNR of DS method and accelerate the development of noninvasive blood components measurement based on DS method.
Electrochemical organic synthesis uses electrons as clean reagents, and has developed rapidly in recent years.This research explores the phenol derivatives and azoles as raw materials to achieve dehydrogenation coupling through electrochemical oxidation, and the construction of C-N bonds for the synthesis of N-azolated aromatic products.Subsequently, the reproducibility of the reaction and the compatibility of substrate were studied to ultimately establish an operation process suitable for undergraduate innovative laboratory research.The experiment involves C-H functionalization reaction, which is the current frontier of organic synthesis scientific research.The reaction operation is simple, safe and efficient.Moreover, the reaction time is controllable via tuning the electricity.The reaction can be monitored by using thin-layer chromatography.The products can be separated and purified by silica gel column chromatography, and the structure can be analyzed by mass spectroscopy and nuclear magnetic resonance spectroscopy.The reaction is based on green organic synthesis to develop practical synthetic methods for nitrogencontaining compounds, by comprehensively applying cross-disciplinary knowledge of organic chemistry and physical chemistry.
For non-invasive measurement of human blood cholesterol concentration, this experiment was carried out on 80 volunteers clinically. In vivo dynamic spectra of fingers were achieved and biochemical examinations of blood components contents including cholesterol were get as soon as possible. BP artificial neural network with inputs of dynamic spectra plus energy of harmonic waves processed by Principal Components Analysis(PCA) was used to establish the model of the total cholesterol values. The correlation between the predicted value and the true value of cholesterol is 96.48%. The maximum relative error is 25.44% and root-mean-square error of prediction is 0.242 6 mmol x L(-1). The results show that PCA can make the process of computing faster and this study is another advance of dynamic spectra.
The extraction of effective information in visible-near-infrared (VIS-NIR) spectroscopy is crucial and difficult for spectral analysis. In this research, an algorithm of wavelet feature extraction based on the Gaussian kernel function (GKF-WTEF) was developed to suppress the influence of external interference on VIS-NIR spectroscopy and improve the accuracy of quantitative analysis. This algorithm takes the root-mean-square error of the prediction set (RMSEP) of the model, which is established by partial least-squares regression, as the optimization criteria. First, the optimal type of wavelet function, the decomposition level, and the Gauss kernel function central frequency band are determined according to the RMSEP. Second, the Gauss kernel function bandwidth is determined by Newton's method. Then, the Hadamard product of the Gaussian kernel function and the wavelet coefficient is obtained. Finally, the wavelet coefficients after the Hadamard product can be reconstructed to obtain the spectral data after feature extraction. In order to verify the effectiveness of this algorithm, the difference in the optical parameters of the polyvinyl chloride material container was used as an external interference source. And the spectrum of Intra-lipid and India-ink mixed solution with different concentrations was collected therein. The volume fraction of India-ink in complex mixed solution was quantitatively analyzed by using the RMSEP and the average relative error of the prediction set as the evaluation criteria. The research results demonstrated that the Gaussian-wavelet transform feature extraction algorithm is an effective pretreatment method, it can satisfactorily suppress the influence of external interference on the spectrum, and it can improve the analytical accuracy of VIS-NIR spectroscopy.
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