ObjectiveTo systematically evaluate the content differences of 4 components in Leonuri Herba granules， reveal the quality fluctuation patterns of products from the same and different manufacturers， providing scientific basis for the optimization of production process and quality control. MethodsHigh performance liquid chromatography-diode array detector-charged aerosol detector（HPLC-DAD-CAD） was employed to determine the contents of 4 components（syringic acid， leonurine hydrochloride， ferulic acid， and stachydrine hydrochloride） in samples from 19 manufacturers（53 batches， 159 boxes）. Additionally， fingerprint profiles were constructed， and the fingerprint dissimilarity（P_S） and relative standard deviation（RSD） of different samples from the same manufacturer were calculated. A principal component analysis（PCA） model was established with P_S and the RSD values of the 4 components as variables to classify the manufacturers. Finally， samples from 5 manufacturers（M1-M5） covering three consistency groups were selected to calculate three quality consistency parameters， namely intra-batch consistency（P_A）， inter-batch consistency（P_B）， and P_S. Then， PCA was performed with P_A， P_B， and P_S of these 5 manufacturers as variables. ResultsThe average total content of the 4 index components per bag across the 19 manufacturers ranged from 41.10 mg to 97.54 mg. Among them， the content of stachydrine hydrochloride（a pharmacopoeial quality control component） was 32.46-72.70 mg per bag， all meeting the requirements of the 2025 edition of the Pharmacopoeia of the People's Republic of China， with RSD of 1.7%-17.1%. The content ranges of the other 3 components were as follows：syringic acid of 1.43-41.92 mg per bag， leonurine hydrochloride of 0.67-11.85 mg per bag， and ferulic acid of 0.11-3.81 mg per bag. Notably， leonurine hydrochloride exhibited the most significant content fluctuation among samples from the same manufacturer（RSD of 4.8%-59.2%）. PCA results showed that the 19 manufacturers could be classified into 3 categories. Samples from 8 manufacturers（M2， M6， M7， M8， M10， M15， M17， M18） demonstrated relatively high consistency， five manufacturers（M3， M9， M12， M13， M14） showed moderate consistency， six manufacturers（M1， M4， M5， M11， M16， M19） exhibited low consistency. The two methods yielded consistent classification results for the 5 representative manufacturers， verifying the reliability of the proposed method. Among these， manufacturer M2 showed the best quality consistency and the highest total content of indicator components among M1-M5. ConclusionThe HPLC-DAD-CAD multi-detector hyphenation technology established in this study enables the accurate detection of 4 components in Leonuri Herba granules. Significant differences in the total content of these four components are observed among products from 19 manufacturers. The application of 2 consistency evaluation methods combined with PCA can effectively classify their consistency into 3 categories， and the classification results of the 2 methods are highly consistent. This study provides scientific basis for the process optimization and quality standard improvement of Leonuri Herba granules.

ObjectiveTo systematically evaluate the content differences of 4 components in Leonuri Herba granules， reveal the quality fluctuation patterns of products from the same and different manufacturers， providing scientific basis for the optimization of production process and quality control. MethodsHigh performance liquid chromatography-diode array detector-charged aerosol detector（HPLC-DAD-CAD） was employed to determine the contents of 4 components（syringic acid， leonurine hydrochloride， ferulic acid， and stachydrine hydrochloride） in samples from 19 manufacturers（53 batches， 159 boxes）. Additionally， fingerprint profiles were constructed， and the fingerprint dissimilarity（P_S） and relative standard deviation（RSD） of different samples from the same manufacturer were calculated. A principal component analysis（PCA） model was established with P_S and the RSD values of the 4 components as variables to classify the manufacturers. Finally， samples from 5 manufacturers（M1-M5） covering three consistency groups were selected to calculate three quality consistency parameters， namely intra-batch consistency（P_A）， inter-batch consistency（P_B）， and P_S. Then， PCA was performed with P_A， P_B， and P_S of these 5 manufacturers as variables. ResultsThe average total content of the 4 index components per bag across the 19 manufacturers ranged from 41.10 mg to 97.54 mg. Among them， the content of stachydrine hydrochloride（a pharmacopoeial quality control component） was 32.46-72.70 mg per bag， all meeting the requirements of the 2025 edition of the Pharmacopoeia of the People's Republic of China， with RSD of 1.7%-17.1%. The content ranges of the other 3 components were as follows：syringic acid of 1.43-41.92 mg per bag， leonurine hydrochloride of 0.67-11.85 mg per bag， and ferulic acid of 0.11-3.81 mg per bag. Notably， leonurine hydrochloride exhibited the most significant content fluctuation among samples from the same manufacturer（RSD of 4.8%-59.2%）. PCA results showed that the 19 manufacturers could be classified into 3 categories. Samples from 8 manufacturers（M2， M6， M7， M8， M10， M15， M17， M18） demonstrated relatively high consistency， five manufacturers（M3， M9， M12， M13， M14） showed moderate consistency， six manufacturers（M1， M4， M5， M11， M16， M19） exhibited low consistency. The two methods yielded consistent classification results for the 5 representative manufacturers， verifying the reliability of the proposed method. Among these， manufacturer M2 showed the best quality consistency and the highest total content of indicator components among M1-M5. ConclusionThe HPLC-DAD-CAD multi-detector hyphenation technology established in this study enables the accurate detection of 4 components in Leonuri Herba granules. Significant differences in the total content of these four components are observed among products from 19 manufacturers. The application of 2 consistency evaluation methods combined with PCA can effectively classify their consistency into 3 categories， and the classification results of the 2 methods are highly consistent. This study provides scientific basis for the process optimization and quality standard improvement of Leonuri Herba granules.

This study investigated a novel coronary knobby scoring balloon through finite element analysis (FEA) and in vitro anti-slippage testing, evaluating its dilation process under various vascular conditions and comparing it with other balloons. The FEA results indicated that in the cases of healthy artery and diseased artery with different stenosis rates, the stress on the vessels caused by the knobby scoring balloon was significantly smaller than that of the scoring balloon, and was close to that of the plain balloon. In vitro anti-slippage testing showed that the slippage distance of a plain balloon was 0.11±0.06 mm, and there was no slippage for knobby scoring balloon under nominal pressure. Knobby scoring balloon can effectively expand calcified lesion while providing anti-slippage function, and has a lower risk of vascular injury.
Finite Element Analysis ; Humans ; Angioplasty, Balloon, Coronary/instrumentation* ; Equipment Design ; Biomechanical Phenomena ; Coronary Vessels

Yigongsan is derived from Xiaoer Yaozheng Zhijue written by QIAN Yi in the Northern Song dynasty， which is the No. 3 formula in the Catalogue of Ancient Famous Classical Formulas（The Second Batch of Pediatrics） released by the National Administration of Traditional Chinese Medicine（TCM） in September 2022， and it can be developed as a class 3.1 new TCM drug. By referring to ancient medical books and modern literature， this study conducted herbal textual research on Yigongsan from five aspects， including historical evolution， origin and processing， dosage conversion， usage and preparation methods， and functional application， then formed the key information table of this formula， in order to provide reference for the development of reference samples and preparations of Yigongsan. Based on the results of the study， it is recommended that Panax ginseng should be removed the basal part of stem（rhizoma）， Poria cocos should be removed the peel， Citrus reticulata should be cut into shreds and Glycyrrhiza uralensis should be used. According to 4.13 g/Qian（钱）， 1 g/slice for ginger， 3 g for each jujube and 300 mL/Zhan（盏）， the doses of Ginseng Radix， Poria， Atractylodis Macrocephalae Rhizoma， Glycyrrhizae Radix et Rhizoma， Citri Reticulatae Pericarpium， Zingiberis Rhizoma Recens， Jujubae Fructus were 1.652， 1.652， 1.652， 1.652， 1.652， 5， 6 g， and the total amount was 19.26 g. The decocting method was to crush the medicinal materials into fine powder with 50-80 mesh， add 300 mL of water and decoct to 210 mL for each dose， then remove the dregs and take it warmly. This formula was recorded in ancient books as the main treatment for the cold-deficiency of spleen and stomach， and Qi stagnation in children with vomiting and diarrhea and lack of appetite. It has been flexibly applied by later generations of physicians， and is often used to treat anorexia， inflammation of the digestive tract， diarrhea and other diseases in children.

ObjectiveTo establish the fingerprint of seven commercially available Yangyin Qingfei preparations， to quantitatively analyze the index components， to evaluate their quality uniformity with multivariate statistical analysis， and to explore the quality differences among different dosage forms. MethodA total of 33 batches of commercially available 7 kinds of Yangyin Qingfei preparations were analyzed by high performance liquid chromatography（HPLC）， the fingerprints were established and the common peaks were identified. Paeoniflorin， verbascoside， harpagoside， glycyrrhizic acid and paeonol were selected as the indicators of quality attributes to quantitatively analyze 33 batches of preparations. Based on the administration methods of Yangyin Qingfei preparations， the daily intake was calculated and the radar charts were poltted， and cluster analysis and principal component analysis were used to explore the quality differences of 7 kinds of Yangyin Qingfei preparations and the quality uniformity among different batches of the same dosage form. ResultThe similarity of fingerprints of 7 dosage forms was 0.248-0.956， suggesting that there were significant differences among different dosage forms of Yangyin Qingfei preparations， and a total of 15 common peaks were calibrated， of which peak 7， peak 8， peak 11， peak 13 and peak 15 were paeoniflorin， verbascoside， harpagoside， glycyrrhizic acid and paeonol， respectively. The radar plots showed that the average total daily intake of large honeyed pills and water honeyed pills was the highest， and the uniformity of pill components was better. The quality of 33 batches of samples was divided into poor quality and high quality by cluster analysis. Principal component analysis showed that the uniformity and dosage form of different dosage forms were significantly different， the oral liquid had the best quality homogeneity with the minimum dispersion. And the content of paeonol in different dosage forms was significantly different， which was the key component of quality control of Yangyin Qingfei preparations. ConclusionYangyin Qingfei large honeyed pills and water honeyed pills show high content and good uniformity， which are relatively preferred dosage forms. Different preparation processes have a great influence on the content of paeonol， and its quality control should be emphasized during production. This study provides a scientific method for the comparison of product quality of different dosage forms of traditional Chinese medicine prescriptions， which is helpful for the development of preferred dosage forms of different prescriptions， and provides a reference for efficient use of medication in the clinical practice.

Objective:To investigate the application prospect of 3D virtual reconstruction and printing technology based on thin-slice CT images in network cloud+dual-track teaching.Methods:A total of 120 medical students who were on probation in The Second Affiliated Hospital of Air Force Medical University from April 2021 to April 2022 were selected as subjects and were randomly divided into experimental group and control group, with 60 students in each group. The students in the experimental group received 3D virtual reconstruction and printing technology combined with network cloud+dual-track teaching, and those in the control group received network cloud+dual-track teaching alone. After 6 months of learning, the teaching effect was compared by closed-book examination, skill operation, speech defense, and questionnaire survey. SPSS 23.0 was used for the t-test and the chi-square test. Results:Compared with the control group in terms of department examination, the experimental group had significantly better scores of theoretical knowledge [(84.25±5.53) vs. (79.43±6.69), P<0.001] and operational skills [(87.68±5.72) vs. (82.97±5.32), P<0.001]. The experimental group had significantly higher scores than the control group in speech [(44.90±2.56) vs. (41.88±2.71), P<0.001] and defense [(45.83±2.62) vs. (43.85±2.56), P<0.001]. The questionnaire survey showed that compared with the control group, the experimental group had significantly higher scores of practical ability, active learning ability, expression ability, practice enthusiasm, and information acquisition ability ( P<0.001). Conclusion:The network cloud+dual-track teaching model assisted by 3D virtual reconstruction and printing technology can significantly improve the objective learning effect and subjective learning initiative of students and has a relatively high value of teaching application and promotion.

The development of famous classical formula compound preparations has been a research hotspot in recent years， carrying great expectations from the government， academia and industry. During the process of its research and development， it reflects many problems related to traditional Chinese medicine （TCM） industry and deserves deep consideration by the academic community. Based on the current status of development of famous classical formulas， this paper summarizes the key problems and made an in-depth analysis. The results show that three key issues should be paid attention. The first is the weakness of basic research in TCM， which affect the healthy development of TCM. The second is the understanding of development of famous classical formula compound preparations is not in-depth， and the formulation of relevant policies needs to be more reasonable. Thirdly， the expectation for the development of famous classical formula compound preparations is too high， which affects the research and development process of the compound preparations. It is hoped that the TCM industry can take this opportunity to face the problems， propose solutions， and form new breakthroughs to promote the development and progress of TCM.

Chinese herbal piece is an important component of the traditional Chinese medicine （TCM） system， and identifying their quality and grading can promote the development and utilization of Chinese herbal pieces. Utilizing deep learning for intelligent identification of Chinese herbal pieces can save time， effort， and cost， while also reasonably avoiding the constraints of human subjectivity， providing a guarantee for efficient identification of Chinese herbal pieces. In this study， a dataset containing 108 kinds of Chinese herbal pieces （14 058 images） was constructed，the basic YOLOv4 algorithm was employed to identify the 108 kinds of Chinese herbal pieces of our database The mean average precision （mAP） of the developed basic YOLOv4 model reached 85.3%. In addition， the receptive field block was introduced into the neck network of YOLOv4 algorithm， and the improved YOLOv4 algorithm was used to identify Chinese herbal pieces. The mAPof the improved YOLOv4 model achieved 88.7%， the average precision of 80 kinds of decoction pieces exceeded 80%， the average precision of 48 kinds of decoction pieces exceeded 90%. These results indicate that adding the receptive field module can help to some extent in the identification of Chinese herbal medicine pieces with different sizes and small volumes. Finally， the average precision of each kind of Chinese herbal medicine piece by the improved YOLOv4 model was further analyzed. Through in-depth analysis of the original images of Chinese herbal medicine pieces with low prediction average precision， it was clarified that the quantity and quality of original images of Chinese herbal medicine pieces are key to performing intelligent object detection. The improved YOLOv4 model constructed in this study can be used for the rapid identification of Chinese herbal pieces， and also provide reference guidance for the manual authentication of Chinese herbal medicine decoction pieces.

Objective To explore the risk factors for vascular invasion and its influence on prognosis of resectable gastric cancer patients by analyzing the clinicopathological features. Methods We retrospectively analyzed the data of 1077 patients with stage Ⅰ-Ⅲ gastric cancer who underwent surgical resection. According to whether vascular invasion occurred, they were divided into LVI positive group (n=672) and LVI negative group (n=405). Logistic univariate and multivariate analyses were used for the relation between clinical pathological features and LVI. Survival analysis was used to study the relation between vascular invasion and survival rate in patients with stage Ⅰ gastric cancer. Results Univariate analysis showed that tumor size, type of differentiation, depth of invasion, lymph node metastasis, TNM stage, Lauren classification, nerve invasion and the increase of CEA, CA125 and CA199 were risk factors for vascular invasion (P < 0.05). Multivariate analysis showed that poor differentiation, deep invasion, lymph node metastasis, nerve invasion and elevated CA724 were independent risk factors for vascular invasion. The 5-year survival rate of stage Ⅰ gastric cancer patients with vascular invasion was significantly lower than that without vascular invasion (P < 0.01). Conclusion Gastric cancer patients with poor differentiation, deep invasion, lymph node metastasis, nerve invasion and elevated CA724 are more prone to vascular invasion. Patients with stage I gastric cancer at risk of vascular invasion should be treated more aggressively.

【Objective】 To establish and verify the vacuum decay method for the tightness inspection of blood products. 【Methods】 The method for inspecting the tightness of blood product was established, and the detection limit, linearity, range, accuracy, precision and durability were verified according to the requirements of methodological verification.The validated method was used to check the tightness of blood product packaging. 【Results】 The detection limit of this method was 2.5 μm, linear correlation coefficient was r=1, the differential pressure of positive sample was within the allowable range of accuracy, and the durability met the requirements.The RSD of results of 6 repeatability tests and 12 intermediate precision tests were both less than 10%, and all validation items met the verification standards. 【Conclusion】 Vacuum decay method can be used to check the tightness of blood products.