Objective:To evaluate the accuracy of the oral healthcare information provided by different large language models (LLM) to explore their feasibility and limitations in the application of oral auxiliary, treatment and health consultation.Methods:This study designed eight items comprising 47 questions in total related to the diagnosis and treatment of oral diseases [to assess the performance of LLM as an artificial intelligence (AI) medical assistant], and five items comprising 35 questions in total about oral health consultations (to assess the performance of LLM as a simulated doctor). These questions were answered individually by the five LLM models (Erine Bot, HuatuoGPT, Tongyi Qianwen, iFlytek Spark, ChatGPT). Two attending physicians with more than 5 years of experience independently rated the responses using the 3C criteria (correct, clear, concise), and the consistency between the raters was assessed using the Spearman rank correlation coefficient, and the Kruskal-Wallis test and Dunn post hoc test were used to assess the statistical differences between the models. Additionally, this study used 600 questions from the 2023 dental licensing examination to evaluate the time taken to answer, scores, and accuracy of each model.Results:As an AI medical assistant, LLM can assist doctors in diagnosis and treatment decision-making, with an inter-evaluator Spearman coefficient of 0.505 ( P<0.01). As a simulated doctor, LLM can carry out patient popularization, with an inter-evaluator Spearman coefficient of 0.533 ( P<0.01). The 3C scores of each model as an AI medical assistant and a simulated doctor were respectively: 2.00 (1.00, 3.00) and 2.00 (2.00, 3.00) points of Erine Bot, 1.00 (1.00, 2.00) and 2.00 (1.00, 2.00) points of HuatuoGPT, 2.00 (1.00, 2.00) and 2.00 (1.00, 3.00) points of Tongyi Qianwen, 2.00 (1.00, 2.00) and 2.00 (1.75, 2.25) points of iFlytek Spark, 3.00 (2.00, 3.00) and 3.00 (2.00, 3.00) points of ChatGPT (full score of 4 points). The Kruskal-Wallis test results showed that, as an AI medical assistant or a simulated doctor, there were statistically differences in the 3C scores among the five large language models (all P<0.001). The average score of the 5 LLMs on the dental licensing examination was 370.2, with an accuracy rate of 61.7% (370.2/600) and a time consumption of 94.6 min. Specifically, Erine Bot took 115 min, scored 363 points with an accuracy rate of 60.5% (363/600), HuatuoGPT took 224 min and scored 305 points with an accuracy rate of 50.8% (305/600), Tongyi Qianwen took 43 min, scored 438 points with an accuracy rate of 73.0% (438/600), iFlytek Spark took 32 min, scored 364 points with an accuracy rate of 60.7% (364/600), and ChatGPT took 59 min, scored 381 points with an accuracy rate of 63.5% (381/600). Conclusions:Based on the evaluation of LLM′s dual roles as an AI medical assistant and a simulated doctor, ChatGPT performes the best, with basically correct, clear and concise answers, followed by Erine Bot, Tongyi Qianwen and iFlytek Spark, with HuatuoGPT lagging behind significantly. In the dental licensing examination, all the 4 LLM, except for HuatuoGPT, reach the passing level, and the time consumpution for answering is significantly reduced compared to the 8 h required for the exam regulations in all of the five models. LLM has the feasibility of application in oral auxiliary, treatment and health consultation, and it can help both doctors and patients obtain medical information quickly. Howere, their outputs carry a risk of errors (since the 3C scoring results do not reach the full marks), so prudent judgment should be exercised when using them.

Objective:To evaluate the accuracy of the oral healthcare information provided by different large language models (LLM) to explore their feasibility and limitations in the application of oral auxiliary, treatment and health consultation.Methods:This study designed eight items comprising 47 questions in total related to the diagnosis and treatment of oral diseases [to assess the performance of LLM as an artificial intelligence (AI) medical assistant], and five items comprising 35 questions in total about oral health consultations (to assess the performance of LLM as a simulated doctor). These questions were answered individually by the five LLM models (Erine Bot, HuatuoGPT, Tongyi Qianwen, iFlytek Spark, ChatGPT). Two attending physicians with more than 5 years of experience independently rated the responses using the 3C criteria (correct, clear, concise), and the consistency between the raters was assessed using the Spearman rank correlation coefficient, and the Kruskal-Wallis test and Dunn post hoc test were used to assess the statistical differences between the models. Additionally, this study used 600 questions from the 2023 dental licensing examination to evaluate the time taken to answer, scores, and accuracy of each model.Results:As an AI medical assistant, LLM can assist doctors in diagnosis and treatment decision-making, with an inter-evaluator Spearman coefficient of 0.505 ( P<0.01). As a simulated doctor, LLM can carry out patient popularization, with an inter-evaluator Spearman coefficient of 0.533 ( P<0.01). The 3C scores of each model as an AI medical assistant and a simulated doctor were respectively: 2.00 (1.00, 3.00) and 2.00 (2.00, 3.00) points of Erine Bot, 1.00 (1.00, 2.00) and 2.00 (1.00, 2.00) points of HuatuoGPT, 2.00 (1.00, 2.00) and 2.00 (1.00, 3.00) points of Tongyi Qianwen, 2.00 (1.00, 2.00) and 2.00 (1.75, 2.25) points of iFlytek Spark, 3.00 (2.00, 3.00) and 3.00 (2.00, 3.00) points of ChatGPT (full score of 4 points). The Kruskal-Wallis test results showed that, as an AI medical assistant or a simulated doctor, there were statistically differences in the 3C scores among the five large language models (all P<0.001). The average score of the 5 LLMs on the dental licensing examination was 370.2, with an accuracy rate of 61.7% (370.2/600) and a time consumption of 94.6 min. Specifically, Erine Bot took 115 min, scored 363 points with an accuracy rate of 60.5% (363/600), HuatuoGPT took 224 min and scored 305 points with an accuracy rate of 50.8% (305/600), Tongyi Qianwen took 43 min, scored 438 points with an accuracy rate of 73.0% (438/600), iFlytek Spark took 32 min, scored 364 points with an accuracy rate of 60.7% (364/600), and ChatGPT took 59 min, scored 381 points with an accuracy rate of 63.5% (381/600). Conclusions:Based on the evaluation of LLM′s dual roles as an AI medical assistant and a simulated doctor, ChatGPT performes the best, with basically correct, clear and concise answers, followed by Erine Bot, Tongyi Qianwen and iFlytek Spark, with HuatuoGPT lagging behind significantly. In the dental licensing examination, all the 4 LLM, except for HuatuoGPT, reach the passing level, and the time consumpution for answering is significantly reduced compared to the 8 h required for the exam regulations in all of the five models. LLM has the feasibility of application in oral auxiliary, treatment and health consultation, and it can help both doctors and patients obtain medical information quickly. Howere, their outputs carry a risk of errors (since the 3C scoring results do not reach the full marks), so prudent judgment should be exercised when using them.

With the advancement of information technology,China has entered the era of multimedia.The"Internet plus"mode and technology have also accelerated medical,health,science popularization,and other information,making it an important channel for people to access such information.It has also emerged as the primary platform for hospital ideological work.Taking the ideological communication of the official account of a tertiary general hospital as an example,this study analyzed the current situation and challenges of the network ideology work of public hospitals in the context of the"Internet plus"and explores the construction of the network ideology work path based on this analysis.

Objective　To analyze the composition, population density, seasonal trends, and insecticide resistance monitoring results of vector mosquitoes in Liaocheng City from 2020 to 2022, providing a reference basis for further mosquito control measures. Methods　According to the "Implementation Plan for National Vector Biomonitoring", adult mosquito monitoring was carried out using mosquito traps and double-layer stacked nets at two national level monitoring points in Dong’e and Chiping. The Bretu Index method was used for monitoring throughout the city, and the immersion method was used for monitoring mosquito insecticide resistance. The monitoring period for adult mosquitoes was from March to November, and for juvenile mosquitoes was from May to October. Results　From 2020 to 2022, a total of 816 mosquito traps were deployed, capturing 4 717 adult mosquitoes with an average density of 5.78 mosquitoes per trap-night. Among them, 4 232 were Culex pipiens pallens, accounting for 89.72% of the total mosquito population, followed by 15 were Anopheles sinensis, accounting for 0.32%; 10 Aedes albopictus, accounting for 0.21%; 460 other mosquito species, accounting for 9.75%. Mosquito density was higher in rural areas compared to urban areas, with the highest density found in livestock sheds, followed by parks, hospitals, farms, and residential areas. Adult mosquito was first observed in May, with the peak activity occurring from June to August. The double-layer net method captures only Aedes albopictus, with an average net trapping index of 2.99 mosquitoes/(net·h), and their activity was concentrated from June to September. The average Brayton Index (BI) from May to October was 15.95, with a peak occurring in July and gradually decreasing after August. Insecticide resistance monitoring found that Culex pipiens pallens in Liaocheng City exhibited low resistance to permethrin, deltamethrin, dithion, and beta cypermethrin, with beta cypermethrin having the highest resistance. Conclusion　The dominant mosquito species in Liaocheng City is Culex pipiens pallens, followed by Aedes albopictus. The peak activity of adult and juvenile mosquitoes is concentrated between July and September, showing a distinct seasonal trend of growth and decline, posing a risk of dengue fever outbreaks. Culex pipiens pallens exhibits resistance to some insecticides, and timely measures should be taken to prevent the outbreak of mosquito-borne infectious diseases.

The prevention and control of novel coronavirus pneumonia (NCP) has already entered a key period . The patients treated in the burn and wound care ward are susceptible to viral infection because of disease, age and other factors, so it is very important to manage the burn and wound care ward during the prevention and control of NCP epidemic. In this paper, combining with the key clinical problems of prevention and control in hospital during the epidemic period of NCP infection, medical evidence, and clinical and management experience, the author formulates prevention and control management strategy of the author’s unit in order to provide reference for prevention and control of burn and wound care ward.

Objective To study endothelial cell damage and changes of parameters related to coagulation and the anticoagulation function in patients with arthropathic psoriasis.Methods A total of 31 psoriasis vulgaris patients,29 arthropathic psoriasis patients and 60 normal controls were enrolled.Coagulation analyzer ALC 9000 was used to measure the parameters related to endothelial damage,coagulation and anticoagulation system in these patients and controls.The correlation between PASI and the tested parameters was assessed.Results Compared with the normal controls,decreased atithrombin activity as well as protein C activity and antigen were observed in 31 psoriasis vulgaris patients and 29 psoriasis arthropathic patients,whereas increased levels of plasminogen activator inhibitor-1 and vW factor were found in these patients.Patients with arthropathic psoriasis had higher levels of plasminogen activator inhibitor-1 and vW factor but a lower level of atithrombin activity as well as protein C activity and antigen than those with psoriasis vulgaris.There was no correlation between PASI and any of the tested parameters.Conclusion There is a more serious damage of endothelial cell in patients with arthropathic psoriasis than psoriasis vulgaris patients,which may lead to the attenuation of anticoagulation function and fibrinolysis activity.Arthropathic psoriasis patients may have a high risk of suffering cardiovascular disease under the background of the inflammation.

Objective To study endothelial cell damage and changes of parameters related to coagulation and the anticoagulation function in patients with arthropathic psoriasis.Methods A total of 31 psoriasis vulgaris patients,29 arthropathic psoriasis patients and 60 normal controls were enrolled.Coagulation analyzer ALC 9000 was used to measure the parameters related to endothelial damage,coagulation and anticoagulation system in these patients and controls.The correlation between PASI and the tested parameters was assessed.Results Compared with the normal controls,decreased atithrombin activity as well as protein C activity and antigen were observed in 31 psoriasis vulgaris patients and 29 psoriasis arthropathic patients,whereas increased levels of plasminogen activator inhibitor-1 and vW factor were found in these patients.Patients with arthropathic psoriasis had higher levels of plasminogen activator inhibitor-1 and vW factor but a lower level of atithrombin activity as well as protein C activity and antigen than those with psoriasis vulgaris.There was no correlation between PASI and any of the tested parameters.Conclusion There is a more serious damage of endothelial cell in patients with arthropathic psoriasis than psoriasis vulgaris patients,which may lead to the attenuation of anticoagulation function and fibrinolysis activity.Arthropathic psoriasis patients may have a high risk of suffering cardiovascular disease under the background of the inflammation.