Objective:To discuss the diagnostic value of miR-26a/b and relationship of this microRNA with clinicopathological features in patients with gastric cancer. Methods:The expression of serum miR-26a/b was detected in 121 patients with gastric cancer and 116 healthy controls using real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). The relationship of miR-26a/b and clinicopathological parameters of patients were analyzed. The receiver operating curve (ROC) was constructed to in vestigate the value of miR-26a/b in the diagnosis of gastric cancer. Results:The relative expression levels of serum miR-26a and miR-26b in patients with gastric cancer were lower than those in the control group (1.60±1.02 vs. 5.35±0.44;1.44±0.71 vs. 5.35±0.71;P<0.05). The relative expression level of miR-26a/b correlated with TNM stage, and the relative expression level of miR-26a also correlated with invasion depth and lymph node metastasis (P<0.05), but not with sex, age, tumor size, or histological type (P>0.05). The area under the ROC curve of miR-26a was 0.828 (95％CI:0.776～0.881), with sensitivity of 73.3％and specificity of 81.0％, while the area under the ROC curve of miR-26b was 0.853 (95％CI:0. 801～0.906), with sensitivity of 68.1％and specificity of 99.2％. Conclusion:The expression of miR-26a/b significantly reduced in patients with gastric cancer, and its expression level correlated with the clinical stage, invasion depth, and lymph node metastasis. MiR-26a/b has potential diagnostic value for gastric cancer.

Based on near infrared spectroscopy and high performance liquid chromatography, this paper established the regression relationship between near infrared spectroscopy and index component content of Huoxiang Zhengqi oral liquid, so as to realize the rapid detection of index component content based on near infrared spectroscopy. Magnolol, honokiol and hesperidin were used as the quality indexes of Huoxiang Zhengqi oral liquid. After using the first derivative and normalization pretreatment method, characteristic variables were screened by CARS, and the correction model was finally established by partial least-squares regression (PLSR) method. The method accuracy was evaluated with the external validation, and the prediction results were tested for significance. The results indicated that when the near infrared spectrum was scanned through the bottle, the model's correlation coefficients of prediction (R_p) were higher than 0.99, the root mean square errors of the prediction models (RMSEP) were all less than 0.008 4, and the relative standard errors of prediction set (RSEP) were all less than 2.83%. There was no significant difference in the predicted results between these two kinds of model. The models established in the non-destructive way have good performance and high prediction accuracy. The rapid and nondestructive way has application value in the quality control of Huoxiang Zhengqi oral liquid.

A high performance liquid chromatography charged aerosol detector (HPLC-CAD) method was established for the simultaneous determination of five saponins (notoginsenoside R1, ginsenoside Rg1, ginsenoside Re, ginsenoside Rb1, Ginsenoside Rd) in Yaobitong capsule, providing a method for quality control. The sample was extracted with methanol and chromatographic separation was performed on a Waters Xbridge Phenol column (150 mm×4.6 mm, 3.5 μm) using acetonitrile-water as the mobile phase with gradient elution at a flow rate of 1.0 mL·min^-1. The column temperature was 30 ℃ and the injection volume was 10 μL. The nebulizer temperature of CAD was 35 ℃ and the air pressure was 60.2 psi, the filtration was 3.6 s, and the collection frequency was 5 Hz. Notoginsenoside R1, ginsenoside Rg1, ginsenoside Re, ginsenoside Rb1 and ginsenoside Rd showed a good linear relationship in the range of 16.96-203.5 μg·mL^-1 (R² = 0.999 3), 54.46-653.5 μg·mL^-1 (R² = 0.999 3), 10.96-131.5 μg·mL^-1 (R² = 0.999 6), 51.50-618.0 μg·mL^-1 (R² = 0.999 0), 15.94-191.3 μg·mL^-1 (R² = 0.999 4), respectively. The average recoveries were 98.96%, 100.8%, 94.76%, 100.1%, 103.1%, and RSDs were 0.87%, 1.46%, 1.85%, 2.06%, 0.96% (n = 6), respectively. The proposed method is accurate, simple and reliable, and can be used for the determination of five saponins in Yaobitong capsule.

Near-infrared spectroscopy(NIRS) combined with band screening method and modeling algorithm can be used to achieve the rapid and non-destructive detection of the traditional Chinese medicine(TCM) production process. This paper focused on the ginkgo leaf macroporous resin purification process, which is the key technology of Yinshen Tongluo Capsules, in order to achieve the rapid determination of quercetin, kaempferol and isorhamnetin in effluent. The abnormal spectrum was eliminated by Mahalanobis distance algorithm, and the data set was divided by the sample set partitioning method based on joint X-Y distances(SPXY). The key information bands were selected by synergy interval partial least squares(siPLS); based on that, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA) and Monte Carlo uninformative variable(MC-UVE) were used to select wavelengths to obtain less but more critical variable data. With selected key variables as input, the quantitative analysis model was established by genetic algorithm joint extreme learning machine(GA-ELM) algorithm. The performance of the model was compared with that of partial least squares regression(PLSR). The results showed that the combination with siPLS-CARS-GA-ELM could achieve the optimal model performance with the minimum number of variables. The calibration set correlation coefficient R_c and the validation set correlation coefficient R_p of quercetin, kaempferol and isorhamnetin were all above 0.98. The root mean square error of calibration(RMSEC), the root mean square error of prediction(RMSEP) and the relative standard errors of prediction(RSEP) were 0.030 0, 0.029 2 and 8.88%, 0.041 4, 0.034 8 and 8.46%, 0.029 3, 0.027 1 and 10.10%, respectively. Compared with the PLSR me-thod, the performance of the GA-ELM model was greatly improved, which proved that NIRS combined with GA-ELM method has a great potential for rapid determination of effective components of TCM.
Algorithms ; Ginkgo biloba ; Least-Squares Analysis ; Plant Leaves ; Spectroscopy, Near-Infrared

The fundamental principle of traditional Chinese medicine(TCM) is holism, and it is crucial for TCM to address the key issue of the "holistic view" of Chinese herbal medicine. While the overall regulatory effects of Chinese herbal medicine have been widely recognized, the holistic internal logic of individual ingredients of Chinese herbal medicines require further clarification. In order to comprehensively understand the mechanism of action of Chinese herbal medicine, this paper combined the holistic view of Chinese herbal medicine with differentiation thinking to explore the intrinsic logical relationships within Chinese herbal medicine. Starting from the perspective of the coexistence of multiple components in Chinese herbal medicine, this paper systematically examined the "self-consistent" phenomenon within single Chinese herbal medicine. This phenomenon refers to the consistent or opposing actions of various components in terms of their physical and chemical properties, pharmacokinetic effects, biological effects, flavors and properties, and TCM efficacy. The paper summarized various logical relationships of syndrome differentiation exhibited by the same Chinese herbal medicine, analyzed the underlying reasons, and focused on analyzing external factors affecting the "self-consistent" phenomenon in the efficacy of Chinese herbal medicine, aiming to better elucidate the theoretical basis of the pharmacological effects of Chinese herbal medicine, further enrich the scientific connotation of the holistic view of Chinese herbal medicine, and provide theoretical guidance for the preparation process, compatibility patterns, and formulation design of Chinese herbal medicine.
Medicine, Chinese Traditional ; Drugs, Chinese Herbal/therapeutic use*

BACKGROUND: Butylphthalide (NBP) and edaravone (EDV) injection are common acute ischemic stroke medications in China, but there is a lack of large real-world safety studies on them. This study aimed to determine the incidence of adverse events, detect relevant safety signals, and assess the risk factors associated with these medications in real-world populations. METHODS: In this study, data of acute ischemic stroke patients were extracted from the electronic medical record database of six tertiary hospitals between January 2019 and August 2021. Baseline confounders were eliminated using propensity score matching. The drugs' safety was estimated by comparing the results of 24 laboratory tests standards on liver function, kidney function, lipid level, and coagulation function. The drugs' relative risk was estimated by logistic regression. A third group with patients who did not receive NBP or EDV was constructed as a reference. Prescription sequence symmetry analysis was used to evaluate the associations between adverse events and NBP and EDV, respectively. RESULTS: 81,292 patients were included in this study. After propensity score matching, the NBP, EDV, and third groups with 727 patients in each group. Among the 15 test items, the incidence of adverse events was lower in the NBP group than in the EDV group, and the differences were statistically significant. The multivariate logistic regression equation revealed that NBP injection was not a promoting factor for abnormal laboratory test results, whereas EDV had statistically significant effects on aspartate transaminase, low-density lipoprotein cholesterol and total cholesterol. Prescription sequence symmetry analysis showed that NBP had a weak correlation with abnormal platelet count. EDV had a positive signal associated with abnormal results in gamma-glutamyl transferase, alanine aminotransferase, aspartate aminotransferase, prothrombin time, and platelet count. CONCLUSIONS In a large real-world population, NBP has a lower incidence of adverse events and a better safety profile than EDV or other usual medications.