Objective: To explore the relative importance of different food attributes and levels in food decision making of school aged children, and to understand their meal preferences, so as to provide the evidence for formulating precise intervention strategies for dietary behaviours of school aged children. Methods: From May to June 2024, a total of 854 children aged 11 to 15 years old were selected from 2 middle schools (each school in urban and rural areas) in both Hubei Province and Anhui Province by stratified cluster random sampling method to conduct a D-optimal discrete choice experiment. The mixed Logit model was used to analyze children s preference for meal attributes and different levels, and to calculate the relative importance (RI) of attributes and willingness to pay (WTP) in meal choices. Results: The included five food attributes had statistical significance on meal choice of school aged children ( P <0.05). The relative importance of food attributes affecting the meal choices of school aged children in descending order were dining mode ( RI =31.26%), food varieties ( RI =30.56%), cooking method( RI =23.84%), taste( RI =8.06%) and price ( RI =6.27%). Among them, school aged children preferred home cooked meals ( β =0.74) (WTP=86.3 yuan),varied foods(grain/tubers+vegetables+fish, meat, eggs and beans) ( β =0.61) (WTP=71.9 yuan), fried/roasted cooking ( β =0.51) and spicy taste ( β =0.33).Price was negatively correlated with meal choices( β =-0.01) ( P <0.05). Based on residential area and body mass index (BMI), the stratified analysis showed that dining mode was highest in the relative importance for rural children with overweight and obese children ( RI =31.28%,34.17%), both of whom preferred home cooked meals ( β =0.76, 0.91), and meals containing fish, meat, eggs and beans with grain/tubers or grain/tubers and vegetables in terms of food choice (area: β =0.53, 0.53 ; BMI: β =0.55, 0.56) ( P <0.05). Conclusions School aged children have different preferences for different attributes of meals. The quality of school meals should be improved,the cost of buying healthy meals should be reduced,targeted family health education should be carried out,and healthy cooking methods should be advocated.

Objective: To explore the clinical dosimetry advantages of automated plan of IMRT for postoperative esophageal cancer and the dose prediction accuracy of the constructed 3D U-Res-Net model． Methods: A total of 110 postoperative esophageal cancer (middle and upper) cases treated by IMRT were considered in the study，of which 90 cases were randomly selected for training of deep learning prediction model．The deep learning prediction model and Auto-Plan module ( Philips pinnacle3 16. 2 ) were used to predict the three-dimension dose distribution and redesigned the remaining 20 cases respectively ，and the results obtained were compared with manual plan. Results : The average DSC value between the deep learning prediction plan and the manual plan was greater than 0. 92 in isodose surface，and the average Hausdorff distance HD95 of the isodose surface was 0. 58－0. 62 cm ; The V20 ，V30 ，Dmean of total lung were slightly lower than those of manual plan (P ＜0. 05 ) for the prediction model， meanwhile，the D2 ，D50 ，Dmean，HI of the target area and V30 of total lungs were better than those of manual plan(P ＜0. 05) for Auto-Plan ; Three-dimensional dose distribution of the three groups and the corresponding DVH curve showed that the three-dimensional dose distribution of the three groups had a little differences，and the DVH curves of the target area and organs at risk had a good agreement． Conclusion Auto-Plan can realize the design of automated plan for postoperative esophageal cancer，while the deep learning prediction model can realize the accurate prediction of the 3D dose distribution.

Objective:To develope a self-adjustable automatic planning method of intensity modulated radiotherapy based on predicted dose, in order to enhance the robustness of automatic planning.Methods:After the patients′ dose by 3D U-Res-Net_B network was predicted, the current dose was calculated based on the last iteration result, then the predicted dose was combined to calculate the target dose and optimized. With all iterations completed or exit conditions satisfied, final treatment plannings would be acquired. A total of 30 cases of rectal cancer were tested to verify the effectiveness of the algorithm.Results:The mean value of planning target volumes′ V100% was (95.03±0.91)% for clinical plans, close to (94.67±1.96)% for automatical plans( P>0.05), and better than (92.90±2.13)% for predicted dose with the statisically significant difference ( t=29.0, P<0.05). Automatic planning′s indexes such as V35 of small intestines, V40 of bladders and V20 - V40 of femoral heads were lower than predicted and clinical ones, with the statisically significant difference( t=4.5-118.0, P<0.05). Discrepancy in other indexes of organs at risk was not statistically significantly different( P>0.05). Conclusions:This method made automatic planning processes more robust and more adaptive to difficult clinical situations.

Objective:To develop a deep learning model for predicting three-dimensional (3D) voxel-wise dose distributions for intensity-modulated radiotherapy (IMRT).Methods:A total of 110 postoperative rectal cancer cases treated by IMRT were considered in the study, of which 90 cases were randomly selected as the training-validating set and the remaining as the testing set. A 3D deep learning model named 3D U-Res-Net was constructed to predict 3D dose distributions. Three types of 3D matrices from CT images, structure sets and beam configurations were fed into the independent input channel, respectively, and the 3D matrix of IMRT dose distributions was taken as the output to train the 3D model. The obtained 3D model was used to predict new 3D dose distributions. The predicted accuracy was evaluated in two aspects: the average dose prediction bias and mean absolute errors (MAEs)of all voxels within the body, the dice similarity coefficients (DSCs), Hausdorff distance(HD 95) and mean surface distance (MSD) of different isodose surfaces were used to address the spatial correspondence between predicted and clinical delivered 3D dose distributions; the dosimetric index (DI) including homogeneity index, conformity index, V50, V45 for PTV and OARs between predicted and clinical truth were statistically analyzed with the paired-samples t test. Results:For the 20 testing cases, the average prediction bias ranged from -2.12% to 2.88%, and the MAEs varied from 2.55% to 5.75%. The DSCs value was above 0.9 for all isodose surfaces, the average MSD ranged from 0.21 cm to 0.45 cm, and the average HD 95 varied from 0.61 cm to 1.54 cm. There was no statistically significant difference for all DIs, except for bladder Dmean. Conclusions:This study developed a deep learning model based on 3D U-Res-Net by considering beam configurations input and achieved an accurate 3D voxel-wise dose prediction for rectal cancer treated by IMRT.

Objective To evaluate the feasibility of utilizing dose-volume histogram (DVH) prediction models of organs at risk (OARs) to deliver automatic treatment planning of prostate cancer.Methods The training set included 30 cases randomly selected from a database of 42 cases of prostate cancer receiving treatment planning.The bladder and rectum were divided into sub-volumes (Ai) of 3 mm in layer thickness according to the spatial distance from the boundary of planning target volume (PTV).A skewed normal Gaussian function was adopted to fit the differential DVH of Ai,and a precise mathematical model was built after optimization.Using the embedded C++ subroutine of Pinnacle scripa,ahe volume of each Ai of the remaining validation set for 12 patients was obtained to predict the DVH parameters of these OARa,ahich were used as the objective functions to create personalized Pinnacle script.Finalla,automatic plans were generated using the script.The dosimetric differences among the original clinical plannina,aredicted value and the automatic treatment planning were statistically compared with paired t-test.Results DVH residual analysis demonstrated that predictive volume fraction of the bladder and rectum above 6 000 cGy were lower than those of the original clinical planning.The automatic treatment planning significantly reduced the V70,V60,V50 of the bladder and the V70 and V60 of the rectum than the original clinical planning (all P＜0.05),the coverage and conformal index (CI) of PTV remained unchangea,and the homogeneity index (HI) was slightly decreased with no statistical significance (P＞ 0.05).Conclusion The automatic treatment planning of the prostate cancer based on the DVH prediction models can reduce the irradiation dose of OARs and improve the treatment planning efficiency.

Objective:To establish the quality standard for Bidouyan granule .Methods: Scutellariae radix and Magnoloae flos were identified by TLC.The content of baicalin was determined by HPLC with a Kromasi 1 C18 column (250 mm ×4.6 mm,5 μm). The mobile phase consisted of methanol-water-phosphoric acid (45:55:0.2) at a flow rate of 1.0 ml· min-1, and the injection volume was 10μl.The detection wavelength was 280 nm and the column temperature was 30℃.Results:The spots in TLC were clear without any interference.The linear range of baicalin was 10.06 μg· ml-1-100.60 μg· ml-1 (r =1.0000).The average recovery was 96.3％,and RSD was 0.7％(n=6).Conclusion:The method is simple and specific with good repeatability , which can be used for the quality control of Bidouyan granule .

Objective:To explore the effect of quality control circle ( QQC) on the error control in PIVAS. Methods:QQC group was established in the department of PIVAS to reduce the errors in intravenous admixture practice. The status was analyzed using the total errors per week as the index, and the improvement target value was calculated by the eighty-twenty rule. The concrete causes for the errors were found out by the method of“brain storm”, and the main causes were confirmed using a fishbone diagram and the eighty-twenty rule, and then some countermeasures were summarized and carried out. The application effect of QQC was judged by the intan-gible and tangible outcomes before and after the activity, and some suggestions for the further improvement were provided. Results:Af-ter the implementation of QQC activity, the number of errors was reduced from 47 per week to 22 per week with the rate of target a-chievement of 104. 1% and the progress rate of 53. 2%. Moreover, QQC showed positive influence on the sense of being masters, co-operation ability, team spirit and sense of responsibility and confidence in the whole staff, and the ability of analyzing, summarizing and solving problems was also enhanced. Conclusion: QQC can significantly reduce the errors in the practice of intravenous admix-ture. The management method is valuable to explore and analyze the deep problems encountered in PIVAS in order to make rational and efficient measures. It is also helpful to improving the service conception of pharmacists and nurses, and enhancing the roles of pharma-cists in quality management and control to ensure medication safety.

OBJECTIVE:To establish the method for the determination of mildronate in human plasma and urine,and to study the pharmacokinetic characteristics in healthy volunteers. METHODS:After precipitating plasma and urine sample,LC-MS/MS method was adopted. Dikma Diamonsil C18 column was used with mobile phase consisted of methanol-water(containing 0.2% for-mic acid,0.3% ammonium acetate)(31∶69,V/V)at the flow rate of 0.6 ml/min. ESI was adopted in MRM mode,by using nega-tive ion. The ion for quantitative analysis were m/z 147.10→58.20 (mildronate) and m/z 152.00→110.10 (internal standard,acet-aminophen). The pharmacokinetic parameters of mildronate with single administration and multiple administration were calculated by using DAS 2.1 software and compared. RESULTS:The linear range of mildronate in plasma were 0.02-20 ng/ml(r=0.999 3) and in urine were 0.05-40 ng/ml(r=0.998 2). The lowest limits of quantitation were 0.02 and 0.05 ng/ml. Precision and recovery met the requirements of biological specimen determination,and endogenous impurities hadn’t effect on the determination. The main pharmacokinetics parameters of low-dose,medium-dose and low-dose(250,500,750 mg)of mildronate in plasma with single ad-ministration were as follows:t1/2 were(3.39±0.81),(5.52±0.57)and(5.32±0.96)h;tmax were(0.80±0.45),(1.38±0.43)and (1.10±0.36)h;cmax were(4.17±1.46),(8.08±1.04)and(15.04±1.86)ng/ml;AUC0-36 h were(24.55±5.81),(45.50±7.07)and (85.60 ± 13.09)ng·h/ml. In the dose range,cmax,AUC0-36 h h had a linear relationship with dose (R2 were 0.974 5 and 0.968 3). The main pharmacokinetic parameters of low-dose of mildronate with multiple administration after keeping stable were as follows:cmin was(0.28 ± 0.10)ng/ml;AUCs was(38.78 ± 4.18)ng·h/ml;cs was(1.62 ± 0.17)ng/ml;DF was(3.81 ± 1.14);t1/2 was(6.17 ± 1.46)h;tmax was(1.20 ± 0.33)h;cmax was(6.46 ± 1.96)ng/ml;AUC0-36 h was(40.33 ± 4.65)ng·h/ml;accumulation factor of cmax and AUC were(1.73±0.90)and(1.64±0.40). Compared with single administration,t1/2,cmax and AUC of mildronate with multiple admin-istration after keeping stable all changed,and tmax had no signifi-cant difference. After single administration,26 h accumulative excretion rate of those groups were (0.004 009 ± 0.001 1)%, (0.004 026±0.001 01)% and(0.003 858±0.000 68)% respec-tively. CONCLUSIONS:Established method is sensitive,accurate and specific,and suitable for the determination of mildronate concentration in human plasma and urine and pharmacokinetics study. Mildronate capsule shows certain accumulation effect in healthy volunteers,and linear pharmacokinetic characteristics.

Objective To evaluate the combination of the mortality in emergency department sepsis (MEDS) score with blood lactate level in the risk stratification of patients with severe sepsis in the emergency department (ED).Methods 665 adult patients with severe sepsis admitted from May 2011 to December 2012 in ED were found to be eligible for the study.MEDS score,acute physiology and chronic health evaluation Ⅱ (APACHE Ⅱ) score,and arterial blood lactate was determined,and the outcomes in 28 days were recorded.Logistic regression analysis was used to evaluate the relationship between each predictive factor score and prognosis.Each predictive factor was compared with the areas under the receiver operating characteristics (ROC) curve (AUC).Results The mortality in 28 days was 34.6％ in 665 patients.The mortality in group of MEDS score 12-27 was significantly higher than that group of MEDS score＜12 [51.0％ (156/306) vs.20.6％ (74/155),x2=28.414,P=0.000].In the meantime,APACHE Ⅱ score and blood lactate level were also significantly higher in group of MEDS score 12-27 than those in group with MEDS score＜12 [APACHE Ⅱ score:26.4 ± 10.6 vs.21.7 ± 8.1,t=-3.555,P=0.002; lactate (mmol/L):4.9 (2.3,9.9)vs.3.9 (1.5,8.9),Z=-2.352,P=0.023].Kaplan-Meier survival analysis showed significantdifference in the two groups (the Log Rank test 36.71,P ＜0.01).The levels of 3 predictive factors were predominantly higher in non-survivors than survivors [MEDS score:14.1 ± 6.7 vs.8.2 ± 4.5,t=-6.929,P=0.000; APACHE Ⅱ score:28.1 ±7.1 vs.22.2± 11.3,t=-6.472,P=0.000; lactate (mmol/L):5.4 (2.9,11.0) vs.3.8 (1.2,9.1),t=-6.472,P=0.004].The AUCs were 0.813,0.706 and 0.727 for MEDS score,APACHE Ⅱ score and blood lactate respectively.The predictive ability for 28-day mortality of MEDS score was better than blood lactate (P=0.008) and APACHE Ⅱ score (P=0.005).The AUC of MEDS score combined with lactate was 0.865,and 28-day mortality prediction was better than MEDS score (AUC 0.865 vs.0.813,P＜0.001).The sensitivity (83.1％),specificity (93.2％),positive prediction value (PPV,62.4％),and negative prediction value (NPV,92.1％) for MEDS score combined with lactate were highest among all predictors.Conclusion MEDS score combined with lactate is a good risk stratification tool for emergency patients with severe sepsis,and its prognostic capability is better than either MEDS score,APACHE Ⅱ score or blood lactate.

OBJECTIVE: To introduce the efficacy of three surgical options for juvenile nasopharyngeal angiofibroma (JNA) resection, and causes of operative bleeding. METHOD: Retrospective analysis of 36 JNAs,three surgical options were used to resect the tumor. There were 15 cases of Class I tumors , using endoscopic nasal cavity approach. Eighteen cases of class II tumors, via extended Caldwell-Luk incision, using the transantral-infratemporal fosse-nasal cavity combined approach for tumor resection. Three cases of class III tumors, the combined intracranial and extra-cranial approach was used to resect the tumor. Meanwhile, report six typical cases for reference. RESULT: Fifteen (15/36) cases of class I tumors, 14 cases were completely resected for the first time without recurrence, 1 recurrence case was re-resected using the same approach. Eighteen (18/36) cases of class II tumors, 13 cases were completely resected for the first time without recurrence, 5 recurrence cases were re-resected totally. Three (3/36) cases of class III were not completely removed, and underwent about 40 Gy radiotherapy with good effects. CONCLUSION Using these three surgical options can effectively remove different types of JNA. When necessary, the intracranial residue can use radiotherapy. Under direct vision to separate the tumor, and effective hemostasis play crucial roles for complete removal of the tumor.
Adolescent ; Angiofibroma ; surgery ; Blood Loss, Surgical ; Child ; Female ; Humans ; Male ; Nasopharyngeal Neoplasms ; surgery ; Retrospective Studies ; Treatment Outcome ; Young Adult