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Background Hypertension is a common chronic disease that seriously endangers the health of the population. The primary-care doctors are the main force in the management of hypertension. However, the doctor-induced therapeutic of inertia greatly affects the achievement of primary-care hypertension control. Objective The aim of this study is to investigate the current status of therapeutic inertia among primary healthcare providers in the diagnosis and treatment process of hypertension, and analyze the causes of therapeutic inertia, providing a reference basis for improving hypertension control rates in China. Methods A simple random sampling method was used to distribute questionnaires to primary healthcare providers in 32 primary healthcare institutions in Tianjin from July to August 2023. The therapeutic inertia in the diagnosis and treatment process of hypertension was evaluated from three dimensions: "soft reasons" and "overestimation of treatment efficacy" as well as "medical insurance policies". Binary Logistic regression analysis was employed to explore the influencing factors of therapeutic inertia. Results A total of 407 questionnaires were distributed in this study, and 386 valid questionnaires were collected, yielding an effective response rate of 94.84%. The average score for primary healthcare providers' knowledge of hypertension diagnosis and treatment was 6 (0.5), with a scoring rate of 61.11% (5.50/9.00). The total score for therapeutic inertia in hypertension management was 48 (7.0), with a scoring rate of 56.55% (45.24/80.00). The scores for the "soft reasons" dimension, "overestimation of treatment efficacy" dimension, and "medical insurance policies" dimension were 26 (4.8), 10 (2.0), and 6 (2.5) respectively, with scoring rates of 51.92% (25.96/50.00), 65.40% (9.81/15.00), and 46.40% (6.96/15.00) respectively. When comparing the average scores of the three dimensions of therapeutic inertia, the "overestimation of treatment efficacy" dimension had the highest score compared to the other two groups (P

Hepatocellular carcinoma (HCC) is a highly vascularized carcinoma, and targeting its neovascularization represents an effective therapeutic approach. Our previous study demonstrated that the baculovirus-mediated endostatin and angiostatin fusion protein (BDS-hEA) effectively inhibits the angiogenesis of vascular endothelial cells and the growth of HCC tumors. However, the mechanism underlying its anti-angiogenic effect remains unclear. Increasing evidence suggests that autophagy has a significant impact on the function of vascular endothelial cells and response to cancer therapy. Hence, the objective of this research was to investigate the correlation between BDS-hEA-induced angiogenesis inhibition and autophagy, along with potential regulatory mechanisms. Our results demonstrated that BDS-hEA induced autophagy in EA.hy926 cells, as evidenced by the increasing number of autophagosomes and reactive oxygen species, accompanied by an upregulation of Beclin-1, LC3-II/LC3-I, and p62 protein expression. Suppression of autophagy using 3-methyladenine attenuated the functions of BDS-hEA-induced EA.hy926 cells, including the viability, proliferation, invasion, migration, and angiogenesis. Moreover, BDS-hEA induced autophagy by downregulating the expression of CD31, VEGF, and VEGFR2, as well as phosphorylated protein kinase B (p-AKT) and phosphorylated mammalian target of rapamycin (p-mTOR), while concurrently upregulating phosphorylated AMP-activated protein kinase (p-AMPK). The in vivo results further indicated that inhibition of autophagy by chloroquine significantly impeded the ability of BDS-hEA to suppress HCC tumor growth in mice. Mechanistically, BDS-hEA prominently facilitated autophagic apoptosis in tumor tissues and decreased the levels of ki67, CD31, VEGF, MMP-9, p-AKT, and p-mTOR while simultaneously enhancing the p-AMPK expression. In conclusion, our findings suggest that BDS-hEA induces autophagy as a cytotoxic response by modulating the AMPK/AKT/mTOR signaling pathway, thereby exerting anti-angiogenic effects against HCC.

Exploring the strategy of integrating rural governance into tourism industry development is to provide industrial support to realize rural revitalization. This paper introduces recurrent neural networks and long and short-term memory neural networks under deep learning techniques, including their specific structures and basic principles, starting from artificial intelligence grading techniques. The basic principle of the attention mechanism is explained, and the components of the basic attention mechanism model structure and the steps of processing data are given. The ATT-LSTM analytical prediction model is jointly constructed using the attention mechanism and the long and short-term memory neural network, and the model’s prediction process and overall structure are given. The ATT-LSTM analysis model was used to analyze the data related to developing rural governance integrated tourism industry using county S as an example. From the satisfaction data, the percentages of very good, good, average, and poor ratings are 9.32%, 24.51%, 39.28%, and 26.89%, respectively. In terms of promotion and publicity, the percentage of visitors introduced by friends and family increased from 25.64% in 2017 to 33.58% in 2020, an increase of 30.97%. This shows that the use of artificial intelligence technology can effectively analyze the impact related to the integration and development of rural governance and the tourism industry and should be complemented by industrial advantages and natural resources to tap into local folk culture and thus promote the prosperous development of the tourism industry.