Abstract To investigate the intervention effects of digital exercise on insufficient physical activity (PA) and sedentary behavior among college students, aiming to enhance PA levels and reduce sedentary behavior. The study systematically reviews the application characteristics of digital exercise intervention, the intervention effects of digital exercise intervention (training websites and applications, social media, wearable devices, emerging interactive technologies) on PA levels and sedentary behavior among college students.Through behavioral modification elements such as goal setting, self monitoring, and feedback support, the approach significantly enhances college students PA levels and improves sedentary behaviors, so as to provide evidence for the design and optimization of future intervention programs.

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 Explore the influencing factors of hearing loss among workers exposed to noise.METHODS A total of 167 noise exposure practitioners undergoing hearing testing in Hangzhou Occupational Disease Prevention and Treatment Center from January 2022 to December 2023 were selected to perform hearing testing on the left and right ears of the patients.Based on the test results,the patients were divided into 123 hearing loss patients(loss group)and 44 non hearing loss patients(control group).The population characteristics,laboratory indicators,noise exposure,and other indicators of the two groups were compared.Logistic regression models were used to analyze the risk factors for hearing loss in noise exposed workers.RESULTS In the 2 000,3 000,4 000,and 6 000 Hz air conduction hearing threshold tests,the hearing threshold of the right side of the loss group patients was higher than that of the control group.In the 500,1 000,2 000,3 000,4 000,and 6 000 Hz air conduction hearing threshold tests,the hearing threshold of the left side of the loss group patients was higher than that of the control group,and the differences were statistically significant(P<0.05).The age of patients in the loss group,the proportion of patients with concurrent chronic diseases,and the proportion of patients with junior high school education or below were all significantly different from those in the control group,and the differences were statistically significant(P<0.05).The length of service and the proportion of patients with liver function loss in the loss group were significantly higher than those in the control group.The proportion of noise protection patients and those who frequently use noise protection equipment in the loss group were significantly lower than those in the control group,and the differences were statistically significant(P<0.05).The results of the Logistic regression model showed that older age,comorbidities with chronic diseases,longer working experience,lack of noise protection,and occasional or never use of noise protection equipment were independent risk factors for hearing loss in noise exposed workers(P<0.05).CONCLUSION There are many factors that can affect the occurrence of hearing loss among workers exposed to noise.Targeted preventive interventions based on high-risk factors can reduce the risk of hearing loss in the population.

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.

ObjectiveThis paper aims to analyze the current status of outcome indicators in randomized controlled trials （RCT） of traditional Chinese medicine （TCM） for treating chronic atrophic gastritis （CAG）， so as to provide references for constructing the core outcome set （COS） of TCM in the treatment of CAG. MethodChina National Knowledge Infrastructure （CNKI）， Wanfang， VIP， SinoMed， PubMed， Embase， and Cochrane Library databases were searched for RCTs of TCM in the treatment of CAG in the last five years. The risk of bias of included studies was evaluated， and the selection status of outcome indicators was statistically analyzed. ResultA total of 150 RCTs were included， with a sample size of 44-398 cases. 164 outcome indicators were reported， with an application frequency of 1 229 times. The outcome indicators were classified into seven indicator domains according to functional attributes， followed by physical and chemical examination （69.41%）， TCM syndrome （12.69%）， symptoms and signs （11.15%）， safety indicators （5.37%）， quality of life （0.65%）， long-term prognosis （0.65%）， and economic evaluation （0.08%）. According to the statistical analysis， there were problems in the selection of outcome indicators in RCTs of TCM for treating CAG， including various indicators， non-standard name reports， unclear primary and secondary indicators， random combination of subjective and objective indicators， neglected patient report outcome indicators， missing long-term prognosis and economic indicators， insufficient reporting of safety indicators， and inconsistent measurement tools and measurement time points. ConclusionIn the past five years， there have been many problems in the selection of outcome indicators in RCTs of TCM for treating CAG. It is necessary to actively promote the construction of the COS of TCM in the treatment of CAG and promote the high-quality development of clinical research of TCM.

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Objective:To re-evaluate the reliability of the conclusions of the systematic reviews (SR)/meta-analysis (MA) of Traditional Chinese Medicine (TCM) in the treatment of functional dyspepsia (FD).Methods:CNKI, CBM, WanFang Data, VIP, PubMed, Cochrane Library, and Embase were searched from the establishment of the database to March 30, 2022. Two researchers independently screened literature and extracted data, and included SRs/MAs in the treatment of FD with TCM. The AMSTAR 2 and GRADE tools were used to evaluate the included the study carried out methodological quality evaluation, outcome evidence quality grading, and descriptive analysis of the main outcome.Results:A total of 28 SRs/MAs were included, with 34 outcome indicators. According to the AMSTAR 2 evaluation results, 21 SRs/MAs were of medium quality, and 7 SRs/MAs were of low quality. The GRADE quality of evidence grading results showed that of the 100 evidence bodies, 13 were of high quality, 58 were of moderate quality, 24 were of low quality, and 5 were of very low quality.Conclusion:TCM in the treatment of FD can improve the clinical efficiency, improve the cure rate, reduce the recurrence rate, and improve the clinical symptoms, but the methodological quality and evidence quality of related SRs/MAs have certain defects, so this conclusion should be treated with caution.

Objective To investigate the molecular mechanism of taurine regulating the polarization of M2 macrophages by mitophagy. Methods THP-1 cells were divided into four groups: M0 group (THP-1 cells were treated by 100 nmol/L phorbol myristate ester for 48 hours to polarize into M0), M2 group (THP-1 cells were induced to polarize into M2 macrophages by 20 ng/mL interferon-4 (IL-4) for 48 hours), M2 combined with taurine groups (added with 40 or 80 mmol/L taurine on the basis of M2 macrophages). The mRNA expression of mannose receptor C type 1(MRC-1), C-C motif chemokine ligand 22(CCL22) and dendritic cell-specific ICAM-3 grabbing non-integrin (CD209) in M2 macrophages were detected by quantitative real-time PCR. Mitochondrial and lysosome probes were used to detect the number of mitochondria and lysosomes by multifunction microplate reader and confocal laser scanning microscope. The level of mitochondrial membrane potential (MMP) was detected by JC-1 MMP assay kit. The expression of mitophagy-related proteins PTEN-induced putative kinase 1 (PINK1) and microtubule-associated protein 1 light chain 3 (LC3) were detected by Western blot analysis. Results Compared with M0 group, the expression of MRC-1, CCL22, CD209 and PINK1, the number of mitochondria and the level of MMP in M2 group were significantly increased, whereas the number of lysosomes and LC3II/LC3I ratio were decreased. Compared with M2 group, the expressions of MRC-1, CCL22 and CD209, the number of mitochondria and the level of MMP in M2 combined with taurine group dropped significantly while the number of lysosomes was found increased, and the protein expression of PINK1 and LC3II/LC3I ratio were also increased. Conclusions The polarization of M2 macrophages is regulated by taurine to prevent excessive polarization via reducing the level of MMP, improving the level of mitophagy, reducing the number of mitochondria, and inhibiting the mRNA expression of polarization markers in M2 macrophages.
Mitophagy ; Taurine ; Macrophages/metabolism* ; Protein Kinases/metabolism* ; RNA, Messenger

Objective:To construct an outpatient counseling record sheet of breastfeeding based on Delphi method, so as to standardize the consultation process of breastfeeding clinics.Methods:Through literature analysis and discussion of the research group, the expert letter questionnaire was designed by themselves. From September to October 2020, two rounds of Delphi letter inquiries were conducted with 16 experts in Hangzhou to determine the outpatient counseling record sheet of breastfeeding.Results:The positive coefficients of two rounds of expert letter inquiries were 100%, the expert authority coefficients were respectively 0.93 and 0.95, and the Kendall's coefficient of concordance were 0.135-0.204 and 0.234-0.563 ( P< 0.05) . The final counseling record sheet constructed included 8 first-level items, 99 second-level items and 94 third-level items. Conclusions:Letter consulting experts have high enthusiasm, high degree of authority and good coordination. The breastfeeding clinic consultation record based on the Delphi method is highly scientific and practical, which can be applied to breastfeeding clinics in various maternal and infant medical institutions.

Objective To explore the operation of grasping forceps and nursing staff made telescopic injection device were used for the clinical effect of Hemostasises thoracoscopic lobectomy. Methods 60 cases of thoracoscopic lobectomy for patients according to the date of surgery were divided into operation group and telescopic grasping forceps injection device group 30 patients were given hemostasia operation grasping forceps extraction hemostatic powder and hemostatic powder into the injection device for telescopic wound hemostasis treatment and preventive treatment, were compared between the two groups in the instrument body, completely hemostatic powder cover the wound time, evacuation time of endoscopic instruments, single hemostatic powder wound coverage, wound bleeding rate, the incidence of bleeding again installed. Results The telescopic injection device group and operation time grasping forceps group into cavity instruments, endoscopic evacuation equipment time showed no significant difference (P>0.05). Hemostatic powder completely cover the wounds of time (24.90 ± 5.90) s and (55.60 ± 25.60) s, there was significant difference between two groups (t=6.401, P<0.01). The single ended wound coverage of blood meal was 86.67%(26/30) and 76.67%(23/30), there was significant difference between two groups (χ2=2.016, P<0.05). Wound bleeding rate was 10.00%(3/30) and 33.33%(10/30), there was statistically significant difference between the two groups (χ2=4.812, P<0.05). The incidence of bleeding again to install powder was 10.0%(3/30) and 93.3%(28/30), there was significant difference between two groups (χ2=41.713, P <0.01). Conclusions The nursing staff made telescopic injection device assisted surgery were thoracoscopic lobectomy of the wound to stop bleeding and prevent rebleeding, wound coverage than grasping forceps, completely cover the wound operation less time than grasper, re install a low incidence of hemostatic powder, the whole process to shorten the operation time.