Objective To optimize the extraction process of the compound herba lysimachiae by orthogonal experiment and response surface method. Methods The sum of the peak areas of multiple representative components in the compound herba lysimachiae was used as the evaluation index. The ultrasonic extraction time, ultrasonic temperature and ethanol ratio were analyzed to optimize the extraction process conditions by orthogonal experiment and Box-Behnken response surface analysis method. Results Ultrasonic extraction time and ethanol ratio are important factors in the extraction process of the compound herba lysimachiae. The effect of ultrasonic temperature in the extraction process is not significant. The optimal extraction condition for compound herba lysimachiaeare is 10 min ultrasonic extraction time at 55 ℃ with 55% ethanol. Conclusion The optimal extraction process parameters obtained by combining orthogonal experiment and Box-Behnken response surface method can be used for the extraction of representative components from the compound herba lysimachiae and pharmaceutical research in the future.

Apoptosis has been considered as the only form of regulated cell death for a long time. However, a novel form of programmed cell death called necroptosis was recently reported. The process of necroptosis is regulated and plays a critical role in the occurrence and development of multiple human diseases. Thus, the study on the molecular mechanism of necroptosis and its effective inhibitors has been an attractive field for researchers. Herein, we introduce the molecular mechanism of necroptosis and focus on the literature about necroptosis drug screening in recent years. In addition, the identification of the critical drug targets of the necroptosis is also discussed.

Objective To observe the value of clinical and CT radiomics features for predicting microsatellite instability-high(MSI-H)status of gastric cancer.Methods Totally 150 gastric cancer patients including 30 cases of MSI-H positive and 120 cases of MSI-H negative were enrolled and divided into training set(n=105)or validation set(n=45)at the ratio of 7∶3.Based on abdominal vein phase enhanced CT images,lesions radiomics features were extracted and screened,and radiomics scores(Radscore)was calculated.Clinical data and Radscores were compared between MSI-H positive and negative patients in training set and validation set.Based on clinical factors and Radscores being significant different between MSI-H positive and negative ones,clinical model,CT radiomics model and clinical-CT radiomics combination model were constructed,and their predictive value for MSI-H status of gastric cancer were observed.Results Significant differences of tumor location and Radscore were found between MSI-H positive and negative patients in both training and validation sets(all P＜0.05).The area under the curve(AUC)of clinical model,CT radiomics model and combination model for evaluating MSI-H status of gastric cancer in training set was 0.760,0.799 and 0.864,respectively,of that in validation set was 0.735,0.812 and 0.849,respectively.AUC of clinical-CT radiomics combination model was greater than that of the other 2 single models(all P＜0.05).Conclusion Clinical-CT radiomics combination model based on tumor location and Radscore could effectively predict MSI-H status of gastric cancer.

Objective To qualitatively analyze the main chemical components in compound Jinqiancao granules by ultra high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS). Methods XBridge BEH C₁₈ column (2.1 mm×100 mm, 2.5 µm) was used for chromatographic separation. The mobile phase was composed of 0.1% formic acid water and 0.1% formic acid-acetonitrile, gradient elution, and the flow rate was 0.4 ml/min. Mass spectrometry was characterized by Quadrupole time-of-flight mass spectrometry (Q-TOF/MS) and positive ion mode scanning. Results Under the optimized LC/MS condition, 47 components in compound Jinqiancao granules were identified. The isomers were distinguished by software calculation. The source of medicinal materials was assigned. Conclusion A rapid and efficient analytical method was established for the identification of chemical components in compound Jinqiancao granules by UHPLC-Q-TOF/MS.