Objective:To construct a general deep learning dose prediction model applicable to radiotherapy for head and neck tumors, establish design methods for artificial intelligence (AI)-assisted radiotherapy plan and evaluate the accuracy of prediction.Methods:Radiotherapy plans of 818 patients who received radiotherapy for head and neck cancers from January 2018 to June 2021 in Cancer Hospital of Chinese Academy of Medical Sciences were enrolled. Patients involved 17 types of common head and neck cancers, and the prescribed dose covered 5 kinds of dose gradients ranging from 54 Gy to 73.92 Gy. And 1-2 cases per each cancer type (31 cases in total) were randomly selected as the validation set, and the remaining 787 cases were used as the training set to build a deep learning head and neck radiotherapy generalized dose prediction model. Then based on the dose prediction results of this model, a program was written to automatically generate inverse optimization condition scripts, which were sent back to the treatment planning system to achieve AI-assisted radiotherapy plan design. Among the patients who received radiotherapy in our hospital from June 2021 to January 2022, 1 patient for each disease type (17 cases in total) was selected to evaluate the AI-assisted plan design program and evaluate its clinical feasibility using paired t-test. Results:Dose prediction model accuracy evaluation revealed that in the 31-case validation set, there was no statistical difference in the evaluation metrics of clinical concern for organs at risks, except for the D 1 cm3 prediction for spinal cord planning risk volume, which was statistically different compared with the clinical reference plan. The AI-assisted plan design program had higher plan quality metric scores (37.88±6.42) than manual plans (35.00±7.63) in 17 test cases ( t=-1.00, P=0.166). The number of manual adjustments to the inverse optimization conditions was reduced from (5.47±2.97) times to (2.76±1.00) times for the AI-assisted plan compared to the manual-only plan ( t=4.12, P<0.001). And the number of outlined dose shaping structures was reduced from 7.35±3.98 to 3.12±1.18 ( t=5.61, P<0.001). Conclusions:The unified universal model of dose prediction established for different head and neck cancers has high accuracy in dose prediction for all types of head and neck tumor plans. The AI-assisted planning method established in this pattern can reduce the clinical workload of physicists and improve the efficiency of their work.

Medical fiber endoscope is one kind of medical device that utilizes fiber technique to realize visual detection for internal organs or cavities.In clinical applications,medical fiber endoscope not only need to complete fiber optic imaging but also need possess the functions of delivering water and air,and operating device.Therefore,its routine management and maintenance for fault is more and more payed attention by the staffs of using medical fiber endoscope in department.The system of delivering water and air is a key structure for some of medical fiber endoscopes,which has higher maintenance matters and frequency of maintaining fault.Based on the above reasons,this research analyzed the working principle of medical fiber endoscopes,and summarized the ideas and methods of repairing common faults through focused on the structural composition of delivering system of water and air of medical fiber endoscopes,so as to improve the management level for this type of medical device.

Objective To investigate the effects of indirect moxibustion on the expressions of DNA methyltransferases(DNMT)and methylation of the brain-derived neurotrophic factor(BDNF)promoter region in uterine tissues of rats with primary dysmenorrhea(PD);To explore the mechanism of epigenetic regulation of indirect moxibustion on PD model rats.Methods A total of 32 female SD rats were randomly divided into blank group,model group,indirect moxibustion group and Western medicine group,with 8 rats in each group.The PD model with cold dampness stagnation syndrome was established using ice-water baths combined with estradiol benzoate and oxytocin.Starting from the first day of modeling,the indirect moxibustion group received salt-partitioned moxibustion at"Shenque"and ginger-partitioned moxibustion at"Guanyuan"for 20 min,while the Western medicine group was gavaged ibuprofen solution.Both interventions were given once a day for 10 days.On day 11,writhing responses were observed and scored after oxytocin injection,Western blot and RT-qPCR were used to detect protein and mRNA expression of BDNF,DNMT3A and DNMT3B in uterine tissue,immunohistochemical staining was used to detect the positive expressions of DNMT3A and DNMT3B in uterine tissue.The DNA methylation of BDNF promoter region in uterine tissue was detected by sulfite sequencing.Results Compared with the blank group,the writhing latency was shortened and the writhing score increased in the model group(P<0.01);the protein and mRNA expressions of BDNF,DNMT3A and DNMT3B in uterine tissue increased(P<0.01),the positive expressions of DNMT3A and DNMT3B increased(P<0.01),and the DNA methylation rate in BDNF promoter region decreased(P<0.01).Compared with the model group,the writhing latency was lengthened and the writhing score decreased in the indirect moxibustion group and Western medicine group(P<0.05,P<0.01);the protein and mRNA expressions of BDNF,DNMT3A and DNMT3B in uterine tissue decreased(P<0.05,P<0.01),the positive expressions of DNMT3A and DNMT3B decreased(P<0.01),and the DNA methylation rate in BDNF promoter region increased(P<0.01).Conclusion Indirect moxibustion at"Shenque"and"Guanyuan"may inhibit the transcription of BDNF by increasing the DNA methylation level of BDNF promoter region,and reduce the expression of BDNF,so as to relieve the pain of PD rats.

Medical fiber endoscope is one kind of medical device that utilizes fiber technique to realize visual detection for internal organs or cavities.In clinical applications,medical fiber endoscope not only need to complete fiber optic imaging but also need possess the functions of delivering water and air,and operating device.Therefore,its routine management and maintenance for fault is more and more payed attention by the staffs of using medical fiber endoscope in department.The system of delivering water and air is a key structure for some of medical fiber endoscopes,which has higher maintenance matters and frequency of maintaining fault.Based on the above reasons,this research analyzed the working principle of medical fiber endoscopes,and summarized the ideas and methods of repairing common faults through focused on the structural composition of delivering system of water and air of medical fiber endoscopes,so as to improve the management level for this type of medical device.

Objective To investigate the effects of indirect moxibustion on the expressions of DNA methyltransferases(DNMT)and methylation of the brain-derived neurotrophic factor(BDNF)promoter region in uterine tissues of rats with primary dysmenorrhea(PD);To explore the mechanism of epigenetic regulation of indirect moxibustion on PD model rats.Methods A total of 32 female SD rats were randomly divided into blank group,model group,indirect moxibustion group and Western medicine group,with 8 rats in each group.The PD model with cold dampness stagnation syndrome was established using ice-water baths combined with estradiol benzoate and oxytocin.Starting from the first day of modeling,the indirect moxibustion group received salt-partitioned moxibustion at"Shenque"and ginger-partitioned moxibustion at"Guanyuan"for 20 min,while the Western medicine group was gavaged ibuprofen solution.Both interventions were given once a day for 10 days.On day 11,writhing responses were observed and scored after oxytocin injection,Western blot and RT-qPCR were used to detect protein and mRNA expression of BDNF,DNMT3A and DNMT3B in uterine tissue,immunohistochemical staining was used to detect the positive expressions of DNMT3A and DNMT3B in uterine tissue.The DNA methylation of BDNF promoter region in uterine tissue was detected by sulfite sequencing.Results Compared with the blank group,the writhing latency was shortened and the writhing score increased in the model group(P<0.01);the protein and mRNA expressions of BDNF,DNMT3A and DNMT3B in uterine tissue increased(P<0.01),the positive expressions of DNMT3A and DNMT3B increased(P<0.01),and the DNA methylation rate in BDNF promoter region decreased(P<0.01).Compared with the model group,the writhing latency was lengthened and the writhing score decreased in the indirect moxibustion group and Western medicine group(P<0.05,P<0.01);the protein and mRNA expressions of BDNF,DNMT3A and DNMT3B in uterine tissue decreased(P<0.05,P<0.01),the positive expressions of DNMT3A and DNMT3B decreased(P<0.01),and the DNA methylation rate in BDNF promoter region increased(P<0.01).Conclusion Indirect moxibustion at"Shenque"and"Guanyuan"may inhibit the transcription of BDNF by increasing the DNA methylation level of BDNF promoter region,and reduce the expression of BDNF,so as to relieve the pain of PD rats.

Objective:To construct a general deep learning dose prediction model applicable to radiotherapy for head and neck tumors, establish design methods for artificial intelligence (AI)-assisted radiotherapy plan and evaluate the accuracy of prediction.Methods:Radiotherapy plans of 818 patients who received radiotherapy for head and neck cancers from January 2018 to June 2021 in Cancer Hospital of Chinese Academy of Medical Sciences were enrolled. Patients involved 17 types of common head and neck cancers, and the prescribed dose covered 5 kinds of dose gradients ranging from 54 Gy to 73.92 Gy. And 1-2 cases per each cancer type (31 cases in total) were randomly selected as the validation set, and the remaining 787 cases were used as the training set to build a deep learning head and neck radiotherapy generalized dose prediction model. Then based on the dose prediction results of this model, a program was written to automatically generate inverse optimization condition scripts, which were sent back to the treatment planning system to achieve AI-assisted radiotherapy plan design. Among the patients who received radiotherapy in our hospital from June 2021 to January 2022, 1 patient for each disease type (17 cases in total) was selected to evaluate the AI-assisted plan design program and evaluate its clinical feasibility using paired t-test. Results:Dose prediction model accuracy evaluation revealed that in the 31-case validation set, there was no statistical difference in the evaluation metrics of clinical concern for organs at risks, except for the D 1 cm3 prediction for spinal cord planning risk volume, which was statistically different compared with the clinical reference plan. The AI-assisted plan design program had higher plan quality metric scores (37.88±6.42) than manual plans (35.00±7.63) in 17 test cases ( t=-1.00, P=0.166). The number of manual adjustments to the inverse optimization conditions was reduced from (5.47±2.97) times to (2.76±1.00) times for the AI-assisted plan compared to the manual-only plan ( t=4.12, P<0.001). And the number of outlined dose shaping structures was reduced from 7.35±3.98 to 3.12±1.18 ( t=5.61, P<0.001). Conclusions:The unified universal model of dose prediction established for different head and neck cancers has high accuracy in dose prediction for all types of head and neck tumor plans. The AI-assisted planning method established in this pattern can reduce the clinical workload of physicists and improve the efficiency of their work.

Objective:Analysis of the influencing factors of maternal oral health care behavior based on the health belief model.Methods:From July to December 2023, a cross-sectional survey was conducted in Peking Union Medical College Hospital on 316 pregnant women who received the health belief questionnaire and self-efficacy scale。 t test and χ2 test were used to analyze the factors affecting the oral health care behavior of pregnant women from the perspective of social psychology. Results:Among the 316 pregnant women included, 110(34.8%) had poor daily oral health care behavior, 120 (38.1%)did not have oral examination before or during pregnancy. The health beliefs of pregnant women in overall oral care were not high, with a score of 6.63+3.23, Median score is 7 (5).Perceived susceptibility to oral diseases ( OR=1.51, 95% CI:1.026-2.213), self-efficacy of daily living ( OR=2.64, 95% CI: 1.384-5.040), self-efficacy of oral examination ( OR=1.74, 95% CI:1.184-2.570) were independent factors of daily oral health care behavior in pregnant women. Health motivation ( OR=2.47, 95% CI:1.474-4.126) and self-efficacy of oral examination ( OR=4.17, 95% CI:2.626-6.619) were independent factors of oral examination behavior before and during pregnancy. Conclusion:Health beliefs of maternal oral health, especially perceived susceptibility, health motivation and self-efficacy are closely related to maternal oral health care behaviors. To improve the health belief and self-efficacy of pregnant women′s oral health care and avoid potential obstacles, which could be conducive to the effective promotion of oral health care for pregnant women.

Objective:Analysis of the influencing factors of maternal oral health care behavior based on the health belief model.Methods:From July to December 2023, a cross-sectional survey was conducted in Peking Union Medical College Hospital on 316 pregnant women who received the health belief questionnaire and self-efficacy scale。 t test and χ2 test were used to analyze the factors affecting the oral health care behavior of pregnant women from the perspective of social psychology. Results:Among the 316 pregnant women included, 110(34.8%) had poor daily oral health care behavior, 120 (38.1%)did not have oral examination before or during pregnancy. The health beliefs of pregnant women in overall oral care were not high, with a score of 6.63+3.23, Median score is 7 (5).Perceived susceptibility to oral diseases ( OR=1.51, 95% CI:1.026-2.213), self-efficacy of daily living ( OR=2.64, 95% CI: 1.384-5.040), self-efficacy of oral examination ( OR=1.74, 95% CI:1.184-2.570) were independent factors of daily oral health care behavior in pregnant women. Health motivation ( OR=2.47, 95% CI:1.474-4.126) and self-efficacy of oral examination ( OR=4.17, 95% CI:2.626-6.619) were independent factors of oral examination behavior before and during pregnancy. Conclusion:Health beliefs of maternal oral health, especially perceived susceptibility, health motivation and self-efficacy are closely related to maternal oral health care behaviors. To improve the health belief and self-efficacy of pregnant women′s oral health care and avoid potential obstacles, which could be conducive to the effective promotion of oral health care for pregnant women.

In order to meet the accuracy requirements of hospitals for abnormal detection of fetal monitor data,a hospital fetal monitor data anomaly detection method based on Euclidean distance was proposed.In this method,according to the abnormal detection method of fetal monitor data in hospitals,the ultrasound Doppler detector was used to collect fetal heart rate signal data,and the fetal heart rate signal denoising method based on adaptive filtering was used to remove the noise components of the collected fetal heart rate signal.The denoised fetal heart rate signal was used as the identification sample of the abnormal fetal heart rate signal identification method based on Euclidean distance method.The Euclidean distance Euclidean distance between the denoised fetal heart rate signal and the normal fetal heart rate signal was analyzed by combining the Euclidean distance method and the strong classifier to analyze whether the virtual sinusoidal distance between the denoised fetal heart rate signal and the normal fetal heart rate signal was greater than the tuned Euclidean distance threshold.Fetal heart rate signal samples greater than the threshold were classified and diagnosed as abnormal monitoring data.The fetal heart rate information collected by the fetal monitor in the hospital was accurate,and the abnormal detection results were valid and reliable.

Background/Aims: Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients. Methods: We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan’s cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray’s cumulative incidence and Cox subdistribution hazards models to analyze HCC development. Results: Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients. Conclusions Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.