Objective: To analyze the temporal variation patterns of sickness absenteeism among primary and secondary school students in Shanghai, so as to explore models suitable for predicting peaks and intensity of absenteeism rates. Methods: The seasonal and trend decomposition using loess (STL) method was used to analyze the seasonal and long term trend changes in sickness absenteeism among primary and secondary school students from September 1 in 2010 to June 30 in 2018, in Shanghai. A hierarchical clustering method based on Dynamic Time Warping (DTW) was employed to classify absenteeism symptoms with similar temporal patterns. Based on historical data, the study constructed and evaluated different time series algorithms and machine learning models to optimize the accuracy of predicting the trend of sickness absenteeism. Results: During the research period, the average new absenteeism rate due to illness was 16.86 per 10 000 person day for every academic year, and the trend of sickness absenteeism exhibited both seasonality and a long term upward trend, reaching its highest point in the 2017 academic year (22.47 per 10 000 person day). The symptoms of absenteeism were divided into three categories: high incidence in winter and spring (respiratory symptoms, fever and general discomfort, etc.), high incidence in summer (eye symptoms, nosebleeds, etc.) and those without obvious seasonality (skin symptoms, accidental injuries, etc.).The constructed time series models effectively predicted the trend of absenteeism due to illness, although the accuracy of predicting peak intensity was relatively low. Among them, the multi layer perceptron (MLP) model performed the best, with an root mean squared error (RMSE) of 8.96 and an mean absolute error (MAE) of 4.37, reducing 36.51% and 39.02% compared to the baseline model. Conclusion Time series models and machine learning algorithms could effectively predict the trend of sickness absenteeism, and corresponding prevention and control measures can be taken for absenteeism caused by different symptoms during peak periods.

Objective To explore the efficiency improvement in segmenting neural network with the application of Transformer + U-Net artificial intelligence (AI) and modeling with the application of Python scripts in three-dimensional (3D) printing brachytherapy. Methods A Transformer + U-Net AI neural network model was constructed, and Adam optimizer was used to ensure rapid gradient descent. Computed tomography or magnetic resonance imaging data of patients were standardized and processed as self-made data sets. The training set was used to train AI and the optimal result weight parameters were saved. The test set was used to evaluate the AI ability. Python programming language was used to write an automated script to obtain the output segmentation image and convert it to the STL file for import. The source applicator and needle could be automatically modeled. The time of automatic segmentation and modeling and the time of manual segmentation and modeling were entered by two people, and the difference was verified by paired t-test. Results Dice similarity coefficient (DSC), mean intersection over union (MIOU), and Hausdorff distance (HD95) were used for evaluation. DSC was 0.9341, MIOU was 0.8762, and mean HD95 was 2.516. The mean time of manual segmentation was 1187 s, and the mean time of AI segmentation was 145 s (P < 0.01). The mean time of manual modeling was 321 s, and the mean time of modeling with Python automated scripts was 18 s (P < 0.01). Conclusion The application of Transformer + U-Net automatic segmentation and Python automated scripts can effectively improve work efficiency in the 3D printing brachytherapy for cervical cancer.

OBJECTIVE To establish the characteristic chromatogram of the volatile oil in the standard decoction of Qingshang juantong decoction， and preliminarily infer the main active components of volatile oil that affect the clinical therapeutic effect. METHODS The volatile oil in the standard decoction of Qingshang juantong decoction was extracted by steam distillation. The ultra-high performance liquid chromatography （UPLC） characteristic chromatograms of 15 batches of samples were established by the Similarity Evaluation System of TCM Chromatographic Fingerprint （2012 edition）， and the similarity evaluation was carried out. The volatile oil of standard decoction was identified by UPLC coupled with quadrupole time-of-flight mass spectrometry （UPLC-Q-TOF/MS）. Then the volatile oil components were analyzed by GC-MS. RESULTS The similarities of UPLC characteristic chromatograms for volatile oil of 15 batches of Qingshang juantong decoction were between 0.949 and 0.997. A total of 12 common peaks were obtained. According to the UPLC-Q-TOF/MS， the main components were methyl eugenol， E-ligustilide， E-butylidenephthalide and so on. A total of 23 components were identified by GC-MS， which were mainly 3，4，5-trimethoxy- methylbenzene， patchouli alcohol， Z-ligustilide and so on. CONCLUSIONS The characteristic chromatograms of the volatile oil in the standard decoction of Qingshang juantong decoction is established， and it is inferred that methyl eugenol， ligustilide， E- butylidenephthalide， patchouli alcohol， 3，4，5-trimethoxy-methylbenzene might be the main active components affecting the clinical therapeutic effect of the volatile oil of Qingshang juantong decoction.

Objective To investigate the feasibility of low-voltage,automatic tube current adjustment(ATCM)and low contrast agent concentration,dose and injection rate combined with full-model iterative re-construction(IMR)in vertebral artery V3-segment three-dimensional CT angiography(3DCTA).Methods A total of 60 patients with suspected upper cervical spine,craniocervical junction lesions undergoing cervical vertebral artery V3 segment 3DCTA in this hospital from November 2019 to May 2020 were selected and divided into the group A and B by adopting the random number table method,30 cases in each group.The group A adopted the ATCM technology of 80 kV,average tube current of 50 mAs,25 mL of contrast agent io-hexol(iodine content 300 mg/mL)combined IMR technology with an injection rate of 3 mL/s,while the group B adopted 120 kV,150 mAs fixed tube current,50 mL injection rate of 5 mL/s contrast agent iopamidol(iodine content 370 mg/mL)combined filter back projection(FBP)reconstruction technology.CT value,noise,signal-to-noise ratio(SNR),contrast noise ratio(CNR)and image sensitivity(FOM)were measured and compared between the two groups and the quality of the resulting images was evaluated.The CT volumet-ric dose index(CTDIvol)and dose-length product(DLP)were recorded,and the effective dose(ED)was cal-culated.Results There was no statistically significant difference in the vertebral arterial CT value between the two groups(P＞0.05),but the noise of the group A was lower than that of the group B(P＜0.05),SNR,CNR and FOM of the group A were greater than those of the group B(P＜0.05).The image quality of the two groups met the requirements of clinical diagnosis[(4.78±0.41)points vs.(4.85±0.35)points],and there was no statistically significant difference in the subjective evaluation of image quality(P＞0.05).The CTDIvol,DLP and ED levels in the group A were lower than those in the group B(P＜0.05).The iodine in-takes of contrast medium in the group A and group B were 7.5 g and 18.5 g,respectively,and the iodine flow rates of contrast agent were 0.9 and 1.85 mg/s,respectively,and compared with group B,the iodine intake and iodine flow rate of the group A were decreased by 59.5％and 51.4％,respectively.Conclusion Low tube voltage ATCM and low contrast concentration,dose and injection rate combined with IMR technology can not only ensure the 3DCTA image quality of vertebral artery V3 segment,but also reduce the radiation dose re-ceived by the patients,and reduce the iodine intake and iodine flow rate of contrast agent.

Objective To explore the effects of the multiple shared decision-making mode using a decision aid manual in conjunction with online labor and delivery decision support on the delivery mode for pregnant women with a scarred uterus.Methods A total of 94 women with scarred uterus who received prenatal care at a tertiary hospital from September 2019 to October 2022 were enrolled and assigned to experimental and control groups using the random number table method.The control group received standard prenatal education,and the experimental group received multiple shared decision-making interventions in addition to standard prenatal education.The degree of conflict in decision-making for delivery,preference for delivery mode,postpartum decision regret,and the final delivery mode between the two groups were compared,respectively.Results Following the multiple shared deci-sion intervention,decision conflict scores in the experimental group were significantly reduced(P<0.001).In the survey on delivery mode preferences,there was a reduction in the number of individuals in the experimental group expressing"uncertainty",and an increase in those choosing vaginal delivery.Ultimately,in the experimental group,30 women(68.2%)underwent cesarean sections,and 14(31.8%)had vaginal deliveries.The level of post-decision regret in the experimental group was lower than that in the control group(P<0.001).Conclusions Multiple shared decision-making for women pregnant with a scarred uterus could reduce the level of decision-making conflict,increase the willingness for vaginal delivery,and assist them in making rational and scientifically informed decisions regarding childbirth.

Objective:To study the current status of longitudinal extrauterine growth restriction (EUGR) in extremely preterm infants (EPIs) and to develop a prediction model based on clinical data from multiple NICUs.Methods:From January 2017 to December 2018, EPIs admitted to 32 NICUs in North China were retrospectively studied. Their general conditions, nutritional support, complications during hospitalization and weight changes were reviewed. Weight loss between birth and discharge > 1SD was defined as longitudinal EUGR. The EPIs were assigned into longitudinal EUGR group and non-EUGR group and their nutritional support and weight changes were compared. The EPIs were randomly assigned into the training dataset and the validation dataset with a ratio of 7∶3. Univariate Cox regression analysis and multiple regression analysis were used in the training dataset to select the independent predictive factors. The best-fitting Nomogram model predicting longitudinal EUGR was established based on Akaike Information Criterion. The model was evaluated for discrimination efficacy, calibration and clinical decision curve analysis.Results:A total of 436 EPIs were included in this study, with a mean gestational age of (26.9±0.9) weeks and a birth weight of (989±171) g. The incidence of longitudinal EUGR was 82.3%(359/436). Seven variables (birth weight Z-score, weight loss, weight growth velocity, the proportion of breast milk ≥75% within 3 d before discharge, invasive mechanical ventilation ≥7 d, maternal antenatal corticosteroids use and bronchopulmonary dysplasia) were selected to establish the prediction model. The area under the receiver operating characteristic curve of the training dataset and the validation dataset were 0.870 (95% CI 0.820-0.920) and 0.879 (95% CI 0.815-0.942), suggesting good discrimination efficacy. The calibration curve indicated a good fit of the model ( P>0.05). The decision curve analysis showed positive net benefits at all thresholds. Conclusions:Currently, EPIs have a high incidence of longitudinal EUGR. The prediction model is helpful for early identification and intervention for EPIs with higher risks of longitudinal EUGR. It is necessary to expand the sample size and conduct prospective studies to optimize and validate the prediction model in the future.

Objective:To analyze the research status of scleral lenses by bibliometric method based on the relevant collection of scleral lenses in the Web of Science database.Methods:Using the scleral lens-related literature collected in the Web of Science Core Collection database in the past 10 years (January 2013 to December 2022) as the object of analysis, bibliometric method and CiteSpace tools were used to conduct visual analysis of the literature.A comprehensive analysis of the volume of literature published, the distribution of countries and institutions, the information of core authors, the distribution of journals, and keyword clustering was performed.Results:A total of 340 articles were retrieved, which were published in 54 journals, with an average of 6.3 articles per journal, involving 301 authors.Research in this area covered 35 countries or regions, and 256 research institutions were involved.Discipline development was mainly in the United States, India, Spain and Australia.The main focus was on scleral lens (scleral contact lens), ocular surface disease, corneal edema, miniature scleral lens, etc.In the past 10 years, the trend of research hot topics in scleral lenses had shifted from the initial study of combining scleral contact lenses with ocular surface diseases to the subsequent study of prosthetic replacement of the ocular surface ecosystem, and the exploration of corneal clearance and shape.From 2013 to 2021, the main focuses were ocular surface diseases, scleral contact lenses, and corneal edema.After 2021, research on ocular surface diseases and keratoplasty declined.From January 2013 to December 2022, emergent keywords related to scleral lens mainly included scleral contact lens, transplantation, anti-host disease, prosthetic device in the first stage, artificial replacement of ocular surface ecosystem and irregular cornea in the second stage, and the research on corneal gap and characteristic shape in the third stage.Optical coherence tomography and corneal topography were commonly used examinations for scleral lens research and fitting.Conclusions:At present, the scleral lens is mainly used for dry eye, corneal diseases, corneal ectasia, keratitis, and corneal transplantation, especially after penetrating keratoplasty and refractive errors.Prosthetic replacement of the ocular surface ecosystem, and the exploration of corneal clearance and shape are the research hotspots in scleral lenses.

Based on WANG Xugao's “thirty methods of treating the liver”， it is believed that the occurrence and development of childhood tic disorders follow the dynamic progression from liver qi disease to liver fire disease and then liver wind disease. The basic pathogenesis of three stages are characterized by binding constraint of liver qi， liver fire hyperactivity， and internal stirring of liver wind. Moreover， liver-blood deficiency and stagnation， and malnutrition of liver yin as the main point in terms of the imbalance of liver qi， blood， yin， and yang should be considered， as well as the imbalance relationship of the five zang organs such as the involvement of other organs and the gradually reach of the other organs. Guided by the principles of “thirty methods of treating the liver”， the treatment of tic disorders in liver qi stage should focus on soothing the liver and rectifying qi， soothing the liver and unblocking the collaterals， using Xiaochaihu Decoction （小柴胡汤） and Sini Powder （四逆散）. The treatment of tic disorders in liver fire stage involves clearing， draining and resolving liver heat， using Longdan Xiegan Decoction （龙胆泻肝汤）， Xieqing Pill （泻青丸）， Danggui Longhui Pill （当归龙荟丸）， and Huagan Decoction （化肝煎）. The treatment of tic disorders in liver wind stage involves extinguishing wind and subduing yang， using Lingjiao Gouteng Decoction （羚角钩藤汤） and Liuwei Dihuang Pill （六味地黄丸）. Throughout the treatment process， attention should be paid to harmonizing the liver's qi， blood， yin， and yang， as well as addressing the pathology of other organs.

【Objective】 To objectively evaluate the quality control level of blood testing process in blood banks through quantitative monitoring and trend analysis, and to promote the homogenization level and standardized management of blood testing laboratories in blood banks. 【Methods】 A quality monitoring indicator system covering the whole process of blood collection and supply, including blood donation service, blood component preparation, blood testing, blood supply and quality control was established. The questionnaire Quality Monitoring Indicators for Blood Collection and Supply Process with clear definition of indicators and calculation formulas was distributed to 17 blood banks in Shandong province. Quality monitoring indicators of each blood bank from January to December 2022 were collected, and 31 indicators in terms of blood testing were analyzed using SPSS25.0 software. 【Results】 The proportion of unqualified serological tests in 17 blood bank laboratories was 55.84% for ALT, 13.63% for HBsAg, 5.08% for anti HCV, 5.62% for anti HIV, 18.18% for anti TP, and 1.65% for other factors (mainly sample quality). The detection unqualified rate and median were (1.23±0.57)% and 1.11%, respectively. The ALT unqualified rate and median were (0.74±0.53)% and 0.60%, respectively. The detection unqualified rate was positively correlated with ALT unqualified rate (r=0.974, P<0.05). The unqualified rate of HBsAg, anti HCV, anti HIV and anti TP was (0.15±0.09)%, (0.05±0.04)%, (0.06±0.03)% and (0.20±0.05)% respectively. The average unqualified rate, average hemolysis rate, average insufficient volume rate and the abnormal hematocrit rate of samples in 17 blood bank laboratories was 0.21‰, 0.08‰, 0.01‰ and 0.02‰ respectively. There were differences in the retest concordance rates of four HBsAg, anti HCV and anti HIV reagents, and three anti TP reagents among 17 blood bank laboratories (P<0.05). The usage rate of ELISA reagents was (114.56±3.30)%, the outage rate of ELISA was (10.23±7.05) ‰, and the out of range rate of ELISA was (0.90±1.17) ‰. There was no correlation between the out of range rate, outrage rate and usage rate (all P>0.05), while the outrage rate was positively correlated with the usage rate (r=0.592, P<0.05). A total of 443 HBV DNA positive samples were detected in all blood banks, with an unqualified rate of 3.78/10 000; 15 HCV RNA positive samples were detected, with an unqualified rate of 0.13/10 000; 5 HIV RNA positive samples were detected, with an unqualified rate of 0.04/10 000. The unqualified rate of NAT was (0.72±0.04)‰, the single NAT reaction rate [(0.39±0.02)‰] was positively correlated with the single HBV DNA reaction rate [ (0.36±0.02) ‰] (r=0.886, P<0.05). There was a difference in the discriminated reactive rate by individual NAT among three blood bank laboratories (C, F, H) (P<0.05). The median resolution rate of 17 blood station laboratories by minipool test was 36.36%, the median rate of invalid batch of NAT was 0.67%, and the median rate of invalid result of NAT was 0.07‰. The consistency rate of ELISA dual reagent detection results was (99.63±0.24)%, and the median length of equipment failure was 14 days. The error rate of blood type testing in blood collection department was 0.14‰. 【Conclusion】 The quality monitoring indicator system for blood testing process in Shandong can monitor potential risks before, during and after the experiment, and has good applicability, feasibility, and effectiveness, and can facilitate the continuous improvement of laboratory quality control level. The application of blood testing quality monitoring indicators will promote the homogenization and standardization of blood quality management in Shandong, and lay the foundation for future comprehensive evaluations of blood banks.

Objective: To understand the relationship between stress and Internet addiction among middle school students in Shanghai, so as to provide a scientific basis for promoting students mental health and preventing Internet addiction. Methods: From May to June 2021, a stratified random cluster sampling method was used to select 6 123 middle and high school students in Shanghai for health risk behavior monitoring. Daily Stressors Evaluation Scale for Urban Secondary School Students was used to evaluate students' stress, and the Internet Addiction Test compiled by Young was used to evaluate students Internet addiction. The correlation between student stress and Internet addiction was analyzed by Kruskal-Wallis H test , Chi square test and multiple Logistic regression. Results: Total stress score of middle school students in Shanghai was 24 (12, 39), academic stress score was 8 (5, 13), physical and psychological stress score was 6 (2, 10), interpersonal stress score was 5 (1, 9), and family stress score was 4 (1, 8). The detection rate of Internet addiction was 4.7%. Multivariate Logistic regression analysis showed that the risk of Internet addiction among middle school students with high levels of stress was 8.05 times(95% CI =4.59-14.12) that of students with low levels of stress( P <0.05). The risk of Internet addiction among middle school students with high levels of academic stress, physical and psychological stress, interpersonal stress and family stress was 5.98(95% CI =3.69-9.70), 6.92(95% CI =4.03-11.88), 4.85(95% CI =3.11-7.55), and 4.18(95% CI =2.73-6.40) times that of students with low levels of stress, respectively( P <0.05). Conclusion The academic stress, physical and psychological stress, interpersonal stress, and family stress among middle school students can all lead to an increased risk of Internet addiction.