Objective:To establish a rapid quantitative model for the determination of moisture,extractives,and content in Pollen Typhae.Methods:Near-infrared spectra of 91 batches of Pollen Typhae samples were collected.Spectral preprocessing was performed using S-G,MSC,SNV,and CWT methods.Variable selection was conducted using CARS,SPA,and VIP methods,and compared with full-spectrum modeling.Partial least squares(PLS)mod-els were established for the quantitative determination of moisture,total ash,extractives,and content.The model performance was evaluated by calculating the coefficient of determination for the calibration set and validation set(R2 c,R2v),root mean square error of calibration and validation(RMSEc,RMSEv),and residual prediction devia-tion(RPD).Results:The PLS models for moisture,extractives,and content in Pollen Typhae showed R2c and R2v values greater than 0.9,RMSEc and RMSEv values approaching 0,and RPD values greater than 3.Conclusion:In this study,near-infrared spectroscopy was used to construct quantitative prediction models for moisture,extractives,typhaneoside,and isorhamnetin-3-O-neohesperidoside content in Pollen Typhae.This method enables rapid detection of the main quality control indicators of Pollen Typhae,providing strong technical support for its quality supervision.

Objective:To establish a rapid quantitative model for the determination of moisture,extractives,and content in Pollen Typhae.Methods:Near-infrared spectra of 91 batches of Pollen Typhae samples were collected.Spectral preprocessing was performed using S-G,MSC,SNV,and CWT methods.Variable selection was conducted using CARS,SPA,and VIP methods,and compared with full-spectrum modeling.Partial least squares(PLS)mod-els were established for the quantitative determination of moisture,total ash,extractives,and content.The model performance was evaluated by calculating the coefficient of determination for the calibration set and validation set(R2 c,R2v),root mean square error of calibration and validation(RMSEc,RMSEv),and residual prediction devia-tion(RPD).Results:The PLS models for moisture,extractives,and content in Pollen Typhae showed R2c and R2v values greater than 0.9,RMSEc and RMSEv values approaching 0,and RPD values greater than 3.Conclusion:In this study,near-infrared spectroscopy was used to construct quantitative prediction models for moisture,extractives,typhaneoside,and isorhamnetin-3-O-neohesperidoside content in Pollen Typhae.This method enables rapid detection of the main quality control indicators of Pollen Typhae,providing strong technical support for its quality supervision.

Objective? To explore the effects of clinical nursing pathway chart in rehabilitation of perioperative patients with thoracoscope pneumonectomy. Methods? From January 2017 to December 2018, we selected 105 patients with thoracoscope pneumonectomy. All of the patients were randomly divided into observation group (n=52) and control group (n=53). Observation group carried out perioperative nursing according to the clinical nursing pathway chart, while control group implemented routine nursing. We compared the pain, respiratory recovery effect and treatment compliance of patients after surgery. Results? The scores of pain of patients in observation group 24 and 48 hours after surgery was (4.85±0.42) and (3.74±0.30) respectively lower than those in control group with statistical differences (t=5.594, 13.105;P＜ 0.05). Five days after surgery, the blood oxygen saturation of observation group and control group was (95.78±0.29)% and (91.73±0.33)% respectively with a statistical difference (t=4.603, P＜ 0.05). Patients with the high level of treatment compliance in intraoperative period accounted for 73.08% in observation group and 45.28% in control group with a statistical difference (Z=4.891,P＜0.05). Conclusions? Application of clinical nursing pathway chart in rehabilitation of perioperative patients with thoracoscope pneumonectomy relieves the postoperative pain and improves rehabilitation effects as well as treatment compliance.

Objective:To explore the macroporous resin adsorption and the membrane separation technologies for the purification of saponins water extract of Anemarrhena asphodeloides. Methods:Ten-fold amount of water was used to extract twice for 120 min each time to extract saponins from Anemarrhena asphodeloides. The macroporous resin adsorption(HP-20,HPD-600,D101,AB-8) and the membrane separation technologies (ceramic microfiltration membranes 0.8 μm and 0.05 μm, and hollow fiber ultrafiltration mem-branes 50,10 and 6 kDa) were adopted to purify the saponins water extract liquid. The physicochemical parameters including electri-cal conductivity,viscosity and turbidity were measured,as well as the contents of total saponins,proteins and polysaccharides were de-termined. Results:The viscosity and turbidity decreased,the value of pH increased and the electrical conductivity of the saponins puri-fication liquid changed irregularly after the membrane filtration. The microfiltration membrane was more advantageous than the ultrafil-tration membrane in removing macromolecular substances. The smaller the pore diameter of microfiltration membrane, the smaller the intercepted molecular weigh,the higher the removal ratio of proteins and the higher the penetration rate of the total saponins,while the polysaccharides content was stable, which was consistent with the results of physicochemical parameters. The ceramic microfiltration membrane could obtain clearer extract,while the ultrafiltration membrane was more suitable for the enrichment of saponins when the in-tercepted molecular weight was 6 kDa. The macroporous resin HPD-600 was the best for the purification of timosaponin water extraction liquid.Conclusion:The selection of membrane for the separation and purification of different substances is particularly important. The change of physicochemical parameters and the content decrease of macromolecular substances have obvious corresponding relationship. Ultrafiltration membrane is better than microfiltration membrane for the purification of timosaponin water extract liquid.