ABSTRACT
Objective: The potency of multi-source information fusion technology was explored to improve the model calibration and prediction performance of Chinese medicine extraction process. Methods: The ethanol extraction process for isolating fat-soluble components from Salvia miltiorrhiza was taken as the research carrier. S. miltiorrhiza from different sources were collected to simulate the fluctuation of materials. The changes of process parameters were simulated by design of experimental (DOE), and the process near infrared spectra (NIRS) were used as the process state variables. The contents of tanshinone IIA, cryptotanshinone, and tanshinone I were determined by HPLC. The raw material properties, process parameters and process state variables were combined as independent variables. The content of effective components in the extract was taken as the dependent variable. The partial least squares (PLS) algorithm was used to establish the quality prediction model of the extracts. Results: The modeling results respectively showed that the RMSECV was 0.172 8 mg/g, RMSEP was 0.031 7 mg/g, RPD was 6.91 (tanshinone IIA); RMSECV was 0.153 4 mg/g, RMSEP was 0.024 2 mg/g, RPD was 4.02 (cryptotanshinone); RMSECV was 0.117 1 mg/g, RMSEP was 0.043 2 mg/g, RPD was 4.76 (tanshinone I). Conclusion: The calibration and prediction performance of multi-source information fusion model are better than the conventional model, which can effectively improve the quality predictability and controllability of S. miltiorrhiza extract.
ABSTRACT
Object To investigate the changes of neurovascular coupling (NVC) in the contralateral cerebral motor region under the action of repetitive transcranial magnetic stimulation (rTMS) at different frequencies. Methods Some experiments were designed, the electroencephalography (EEG) signals and the near-infrared spectra (NIRS) of the subjects were obtained under different rTMS stimulation frequencies, and EEG power spectrum of each frequency band and NIRS blood oxygen signals to the contralateral movement area were computed and the change characteristics and correlation were analyzed.Results For different stimulation frequencies, the energy of each frequency band of EEG increased after the stimulation, and then decreased rapidly. The oxyhemoglobin (HbO2) concentration was decreased during stimulation, and then raised. The change rate of the two signals varied with different stimulation frequencies, while the change trend was the same.The EEG power spectrum was negatively correlated with the change of HbO2 concentration after stimulation, and it had delayed effect in varying degrees in the period after stimulation.Conclusion The effect of rTMS on the coupling of nerves and vessels in the contralateral cerebral motor region can be reliably revealed by the study of EEG combined with NIRS. This study will be helpful to the development of effective RTMS treatment parameters, and the results are expected to be applied in clinical treatment.
ABSTRACT
Biomass is an important parameter reflecting the fermentation dynamics. Real-time monitoring of biomass can be used to control and optimize a fermentation process. To overcome the deficiencies of measurement delay and manual errors from offline measurement, we designed an experimental platform for online monitoring the biomass during a 1,3-propanediol fermentation process, based on using the fourier-transformed near-infrared (FT-NIR) spectra analysis. By pre-processing the real-time sampled spectra and analyzing the sensitive spectra bands, a partial least-squares algorithm was proposed to establish a dynamic prediction model for the biomass change during a 1,3-propanediol fermentation process. The fermentation processes with substrate glycerol concentrations of 60 g/L and 40 g/L were used as the external validation experiments. The root mean square error of prediction (RMSEP) obtained by analyzing experimental data was 0.341 6 and 0.274 3, respectively. These results showed that the established model gave good prediction and could be effectively used for on-line monitoring the biomass during a 1,3-propanediol fermentation process.
ABSTRACT
Scutellaria baicalensis is a common and important medicinal plant in China, facing with reducing sharply in wild resources. To meet the needs in Chinese herbwouls medicine market and clinical application, S. baicalensis has been widely cultivated in Ningxia, Hebei, Shanxi, and Gansu et al. HPLC finger-print and near-infrared were studied in the research to evaluate quality difference of S. baicalensis in four districts. The results showed that the similarity of HPLC finger-print of 12 cultivated S. baicalensis and reference crude herb is more than 0.961, and the other is more than 0.983. On the other hand, paired sample t-test indicated there has no significant difference between the common peaks' area of 12 cultivated S. baicalensis and reference crude herb. It was verified that 12 cultivated S. baicalensis has highly consistency with reference crude herb. On the basis of chromatographic finger-print and near-infrared spectrum, the study applied paired sample t-test to verify analysis results, which could avoid erroneous judgment induced by indefinite threshold values in the similarity of chromatographic finger-print and provide reliable basis for the analysis results. Meanwhile, it also provides a new idea for improving the quality control method of Chinese medicinal materials by comparative study about two comprehensive detection means.