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Objective To evaluate clinical efficacy of the combination of Vonoprazan and high-dose Amoxicillin in the initial eradication treatment of Helicobacter pylori(Hp). Methods Select 200 patients with Hp infection who have not undergone Hp eradication treatment in the past as the research subjects. All patients were randomly divided into the observation group (n = 100) and control group (n = 100) using random number table method. In the observation group, a combination regimen of Vonoprazan (20 mg twice a day) and Amoxicillin (1 g three times a day) was given for 14 days. In the control group, a bismuth quadruple therapy was delivered for 14 days, which included Esomeprazole (20 mg twice a day), Bismuth Potassium Citrate (220 mg twice a day), Amoxicillin (1 g twice a day) and Clarithromycin (0.5 g twice a day). The Hp eradication rate and incidence of adverse reactions after medication were compared between two groups. Results Of 200 patients, 11 patients were excluded from subsequent analysis, including 8 cases lost to follow-up and 3 cases with poor compliance of medication. The remaining 189 patients (96 in the observation group and 93 in the control group) completed the entire procedure. According to intention-to-treat (ITT) and per-protocol (PP) set analyses, the Hp eradication rate in the observation group was significantly higher than that in the control group (91.0% vs. 79.0%,PITT = 0.017; 94.8% vs. 84.9%,PPP = 0.024). The incidence of adverse reactions did not significantly differ between two groups (4% vs. 5%, χ2 < 0.001,P > 0.999). Conclusion The combination therapy of Vonoprazan and high-dose Amoxicillin is an efficacious and safe therapeutic option for patients with initial Hp infection, which is worthy of promotion in grassroot-level hospitals. [ABSTRACT FROM AUTHOR]

In order Lo predicl Lhe nonlinear effecl of receiver in complex eleclromagnelic environmenl, a nonlinear behavior model of receiver with memory effect is constructed based on real - value time - delay radial basis function neural network. The K - means clustering algorithm and the orthogonal least square method are respectively used to select and learn the center of the hidden layer and weight of the model, and the model is trained with the input and output measured data of the receiver. The model is verified by the in - phase and quadrature components of wideband signals. The simulation results are in good agreement with the measured data, and the normalized mean square errors of the model reaches -41. 88 dB. The verification results show that the neural network model has fast convergence speed, good modeling accuracy and generalizalion ability. [ABSTRACT FROM AUTHOR]

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