Objective To explore the application of nerve ultrasound score (DCEC score) in the diagnosis of diabetic peripheral neuropathy. Methods Seventy－three patients with type 2 diabetes were divided into subclinical diabetic peripheral neuropathy group (n=16) and diabetic peripheral neuropathy group (n=58). DCEC score was obtained from all participants. The cut－off value of DCEC score was defined by the receiver operating characteristic (ROC) curve, and its sensitivity, specificity, accuracy, positive likelihood ratio and negative likelihood ratio were analyzed. Results When the DCEC score was ≥14.5, 50 cases of diabetic peripheral neuropathy were diagnosed. The sensitivity was 81.0% , the specificity was 80.0% , the accuracy was 80.8% , the positive likelihood ratio was 4.05, and the negative likelihood ratio was 0.24. Conclusion DCEC score can effectively diagnose diabetic peripheral neuropathy which can be used as a new method to diagnose diabetic peripheral neuropathy.

OBJECTIVE To explore the pharmacodynamic related substances and mechanism of Weining San(WNS) against gastric ulcer(GU) according to fingerprint and network pharmacology. METHODS Twelve batches of WNS fingerprints were established by HPLC, and methodological investigation was carried out. Combined with reference substances, characteristic peaks were identified, pharmacodynamic related substances were screened, and network pharmacological analysis was carried out. Using TCMIP and Swiss Target Prediction database to retrieve component targets; Using OMIM, GeneCards and Drugbank databases to retrieve GU disease targets, taking the intersection targets of components and diseases, using String database to construct protein-protein interaction network diagram, and analyzing topological parameters; Using Cytoscape 3.8.2 software to construct "component-disease-target" network diagram; GO and KEGG enrichment analysis of intersection targets were carried out by Metascape website. Then the alcoholic GU mouse model was established by intragastric administration of absolute ethanol to verify the results of network pharmacology prediction. RESUITS　The precision, stability and repeatability of HPLC fingerprint method were good. By comparison and comprehensive analysis of control substances, notoginsenoside R1, ginsenoside Rg1, militarine, ginsenoside Rb1, schisandrin, schisandrol B, deoxyschizandrin and schisantherin A were identified as pharmacodynamic related substances in WNS, which may play their role by regulating core targets such as AKT1, IL-6, STAT3, TNF, IL1B and key signal pathways such as PI3K-Akt and JAK-STAT. The gastric ulcer index, ulcer inhibition rate and HE staining showed that WNS could improve gastric mucosal injury in GU mice. The results of ELISA, WST-1 and TBA showed that WNS could decrease the levels of TNF-α, IL-6, IL-1β and MDA, and increase the levels of SOD and PGE2, suggesting that the anti-GU effect of WNS was related to the inhibition of inflammatory reaction and oxidative stress mechanism, which further verified the prediction of network pharmacology. CONCLUSION This study combines fingerprint analysis, network pharmacology, and animal experimental validation to explore the pharmacodynamic related substances and mechanisms of WNS anti-GU efficacy, providing reference for quality control and clinical research of WNS.