Objective: To analyze the effects of health literacy on overweight and obesity among primary school students and their parents in terms of salt, oil and sugar reduction (referred to as the "three reductions"), so as to provide a theoretical basis for the development of obesity control measures. Methods: From March to April 2024, a total of 1 022 fourthgrade primary school students and 913 parents were surveyed in 24 classes in six counties in Shandong Province using multistage cluster random sampling, and physical measurements of primary school students were conducted. Pearsons correlation analysis and ordered multivariate Logistic regression were used to investigate the associations between health literacy of primary school students and their parents with overweight and obesity among children. Results: The detection rates of overweight and obesity primary school students in Shandong Province were 14.87% and 24.66%, respectively, with significant sex difference in obesity rate (29.46% for boys and 19.76% for girls) (χ2=12.93, P<0.01). In addition to students reducing oil scores, parental reducing salt,reducing oil,reducing sugar, comprehensive health literacy scores and students reducing salt,reducing sugar and comprehensive health literacy scores showed a negative relationship with students overweight and obesity (r=-0.10, -0.08, -0.07, -0.10, -0.04, -0.07, -0.03, P<0.05). The overweight and obesity rates among primary school students with high parental reducing salt,reducing oil,reducing sugar and composite health literacy scores were lower (OR=0.69, 0.69, 0.71, 0.63, P<0.05); and the overweight and obesity rate among students with high parental and low parental and high and low parental health literacy scores were lower (OR=0.68, 0.57, P<0.05). Conclusion Improving health literacy regarding "three reductions" for parents and children, especially parents, can effectively reduce the risk of childhood overweight and obesity.

Methods: Seventy-five patients with atlas fracture were included from January 2015 to December 2020. Based on the anatomy of the fracture line, atlas fractures were divided into three types. Each type was divided into two subtypes according to the fracture displacement. Unweighted Cohen kappa coefficients were applied to evaluate the reliability and reproducibility. Results: According to the new classification, 17 cases of type A1, 12 of type A2, seven of type B1, 13 of type B2, 12 of type C1, and 14 of type C2 were identified. The K-values of the interobserver and intraobserver reliability were 0.846 and 0.912, respectively, for the new classification. The K-values of interobserver reliability for types A, B, and C were 0.843, 0.799, and 0.898, respectively. The K-values of intraobserver reliability for types A, B, and C were 0.888, 0.910, and 0.935, respectively. The mean K-values of the interobserver and intraobserver reliability for subtypes were 0.687 and 0.829, respectively. Conclusions The new classification of atlas fractures can cover nearly all atlas fractures. This system is the first to evaluate the severity of fractures based on the C1 articular facet and fracture displacement and strengthen the anatomy ring of the atlas. It is concise, easy to remember, reliable, and reproducible.

Methods: Seventy-five patients with atlas fracture were included from January 2015 to December 2020. Based on the anatomy of the fracture line, atlas fractures were divided into three types. Each type was divided into two subtypes according to the fracture displacement. Unweighted Cohen kappa coefficients were applied to evaluate the reliability and reproducibility. Results: According to the new classification, 17 cases of type A1, 12 of type A2, seven of type B1, 13 of type B2, 12 of type C1, and 14 of type C2 were identified. The K-values of the interobserver and intraobserver reliability were 0.846 and 0.912, respectively, for the new classification. The K-values of interobserver reliability for types A, B, and C were 0.843, 0.799, and 0.898, respectively. The K-values of intraobserver reliability for types A, B, and C were 0.888, 0.910, and 0.935, respectively. The mean K-values of the interobserver and intraobserver reliability for subtypes were 0.687 and 0.829, respectively. Conclusions The new classification of atlas fractures can cover nearly all atlas fractures. This system is the first to evaluate the severity of fractures based on the C1 articular facet and fracture displacement and strengthen the anatomy ring of the atlas. It is concise, easy to remember, reliable, and reproducible.

Objective To establish an HPLC method to determine the concentration of inositol nicotinate（IN） in rat skin, and study the pharmacokinetic characteristics of IN after transdermal administration of heparin sodium inositol nicotinate cream in rats. Methods HPLC method was used to establish a simple and rapid analytical method for the determination of IN concentration in the skin of rats at different time points after administration. The established method was used to study the pharmacokinetics of IN after transdermal administration of heparin sodium inositol nicotinate cream in rats, and the pharmacokinetic parameters were fitted with DAS software. Results The linearity of the analytical method was good in the concentration range of 0.25-20 μg/ml, the quantitative limit was 0.25 μg/ml, and the average recovery rate was 96.18%. The pharmacokinetic parameters of IN after transdermal administration of heparin sodium inositol nicotinate cream in rats were as follows: t_1/2 was （4.555±2.054） h, T_max was （6±0）h, C_max was （16.929±2.153）mg/L, AUC_0−t was （150.665±16.568） mg·h /L ,AUC_0−∞ was （161.074±23.917） mg·h /L, MRT_（0−t） was （9.044±0.618）h, MRT_{（0−∞）} was （10.444±1.91） h, CLz/F was （0.19±0.03） L/（h·kg）, and Vz/F was （1.19±0.437） L/（h·kg）. Conclusion IN could quickly penetrate the skin and accumulate in the skin for a long time, which was beneficial to the pharmacological action of drugs on the lesion site for a long time. The method is simple, rapid, specific and reproducible, which could be successfully applied to the pharmacokinetic study of IN after transdermal administration in rats.

Methods: Seventy-five patients with atlas fracture were included from January 2015 to December 2020. Based on the anatomy of the fracture line, atlas fractures were divided into three types. Each type was divided into two subtypes according to the fracture displacement. Unweighted Cohen kappa coefficients were applied to evaluate the reliability and reproducibility. Results: According to the new classification, 17 cases of type A1, 12 of type A2, seven of type B1, 13 of type B2, 12 of type C1, and 14 of type C2 were identified. The K-values of the interobserver and intraobserver reliability were 0.846 and 0.912, respectively, for the new classification. The K-values of interobserver reliability for types A, B, and C were 0.843, 0.799, and 0.898, respectively. The K-values of intraobserver reliability for types A, B, and C were 0.888, 0.910, and 0.935, respectively. The mean K-values of the interobserver and intraobserver reliability for subtypes were 0.687 and 0.829, respectively. Conclusions The new classification of atlas fractures can cover nearly all atlas fractures. This system is the first to evaluate the severity of fractures based on the C1 articular facet and fracture displacement and strengthen the anatomy ring of the atlas. It is concise, easy to remember, reliable, and reproducible.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Objective: To investigate the iodine nutrition status of children in water borne iodine excess areas in Hebei Province, so as to provide references for scientific prevention and control of water borne iodine excess hazards. Methods: From March to September each year during 2018 to 2023, a cross sectional survey was conducted in 39 water borne iodine excess counties (measured in 2017) from 5 cities (Cangzhou, Hengshui, Xingtai, Handan and Langfang) in Hebei Province. The survey included the detection of iodine content in residents drinking water, the measurement of thyroid volume in children aged 6-12, the detection of salt iodine and urinary iodine. The iodine nutrition status and water iodine distribution of 6-12 year-old children were evaluated from different perspectives such as years, gender, and age. Kruskal-Wallis H- test, Mann-Whitney U test and Chi square test were used for group comparison. Results: A total of 38 755 children were surveyed from 2018 to 2023, and 1 270 drinking water samples were tested across the province. The mass volume concentration of iodine in water showed a decreasing trend over the years ( Z= -30.87, P <0.01). Among 38 470 salt samples monitored from children s home, 24 790 were not non iodized salt, with a non iodized salt rate of 64.44%. A total of 31 989 urine samples were collected from children aged 8-10 years, with the median urine iodine was 245.94 μg/L. Comparing the results of urinary iodine in children from different years, the median urinary iodine from 2018 to 2023 were 328.0, 339.3, 267.8, 279.1, 291.3, 186.5 μg/L, respectively, with statistically significant differences ( H= 4 138.40 , P <0.01). Further pairwise comparisons showed that the median urinary iodine of children in 2023 was lower than in all other years ( Z =-51.59 to -11.41, all P <0.01). Among children aged 6-12 years, 1 150 cases of goiter were detected and the rate of goiter was 3.0%; and the goiter rates in boys and girls were 2.8% and 3.1%, with no significant difference between the sexes ( χ 2= 2.76, P >0.05). There were significant differences in the rate of goiter among different years and ages ( χ 2=324.02, 191.61, both P <0.05). Conclusions With the progress of water reform in water borne iodine excess areas of Hebei Province, children s iodine nutrition has reduced from excessive state to suitable state. It is necessary to continue to expand the coverage of water based iodine reduction projects, and strengthen the monitoring of iodine nutrition status of key populations in water borne iodine excess areas.

ObjectiveTo evaluate the efficacy and safety of Xiaoji Hufei Formula in protecting children with close contact exposure to influenza， and to provide reference and evidence-based support for better clinical prevention and treatment of influenza in children. MethodsA multicenter， prospective， non-randomized， parallel， controlled trial was conducted from October 2021 to May 2022 in five hospitals， including Dongfang Hospital of Beijing University of Chinese Medicine. Confirmed influenza cases and influenza-like illness （ILI） cases were collected， and eligible children with close contact exposure to these cases were recruited in the outpatient clinics. According to whether the enrolled close contacts were willing to take Xiaoji Hufei formula for influenza prevention， they were assigned to the observation group （108 cases） or the control group （108 cases）. Follow-up visits were conducted on days 7 and 14 after enrollment. The primary outcomes were the incidence of ILI and the rate of laboratory-confirmed influenza. Secondary outcomes included traditional Chinese medicine （TCM） symptom score scale for influenza， influenza-related emergency （outpatient） visit rate， influenza hospitalization rate， and time to onset after exposure to influenza cases. ResultsA total of 216 participants were enrolled， with 108 in the observation group and 108 in the control group. Primary outcomes： （1） Incidence of ILI： The incidence was 12.0% （13/108） in the observation group and 23.1% （25/108） in the control group， with the observation group showing a significantly lower incidence （χ²=4.6， P<0.05）. （2） Influenza confirmation rate： 3.7% （4/108） in the observation group and 4.6% （5/108） in the control group， with no statistically significant difference. Secondary outcomes： （1） TCM symptom score scale： after onset， nasal congestion and runny nose scores differed significantly between the two groups （P<0.05）， while other symptoms such as fever， sore throat， and cough showed no significant differences. （2） Influenza-related emergency （outpatient） visit rate： 84.6% （11 cases） in the observation group and 96.0% （24 cases） in the control group， with no significant difference. （3） Time to onset after exposure： The median onset time after exposure to index patients was 7 days in the observation group and 4 days in the control group， with a statistically significant difference （P<0.05）. ConclusionIn previously healthy children exposed to infectious influenza cases under unprotected conditions， Xiaoji Hufei formula prophylaxis significantly reduced the incidence of ILI. Xiaoji Hufei Formula can be recommended as a specific preventive prescription for influenza in children.

ObjectiveTo evaluate the efficacy and safety of Xiaoji Hufei Formula in protecting children with close contact exposure to influenza， and to provide reference and evidence-based support for better clinical prevention and treatment of influenza in children. MethodsA multicenter， prospective， non-randomized， parallel， controlled trial was conducted from October 2021 to May 2022 in five hospitals， including Dongfang Hospital of Beijing University of Chinese Medicine. Confirmed influenza cases and influenza-like illness （ILI） cases were collected， and eligible children with close contact exposure to these cases were recruited in the outpatient clinics. According to whether the enrolled close contacts were willing to take Xiaoji Hufei formula for influenza prevention， they were assigned to the observation group （108 cases） or the control group （108 cases）. Follow-up visits were conducted on days 7 and 14 after enrollment. The primary outcomes were the incidence of ILI and the rate of laboratory-confirmed influenza. Secondary outcomes included traditional Chinese medicine （TCM） symptom score scale for influenza， influenza-related emergency （outpatient） visit rate， influenza hospitalization rate， and time to onset after exposure to influenza cases. ResultsA total of 216 participants were enrolled， with 108 in the observation group and 108 in the control group. Primary outcomes： （1） Incidence of ILI： The incidence was 12.0% （13/108） in the observation group and 23.1% （25/108） in the control group， with the observation group showing a significantly lower incidence （χ²=4.6， P<0.05）. （2） Influenza confirmation rate： 3.7% （4/108） in the observation group and 4.6% （5/108） in the control group， with no statistically significant difference. Secondary outcomes： （1） TCM symptom score scale： after onset， nasal congestion and runny nose scores differed significantly between the two groups （P<0.05）， while other symptoms such as fever， sore throat， and cough showed no significant differences. （2） Influenza-related emergency （outpatient） visit rate： 84.6% （11 cases） in the observation group and 96.0% （24 cases） in the control group， with no significant difference. （3） Time to onset after exposure： The median onset time after exposure to index patients was 7 days in the observation group and 4 days in the control group， with a statistically significant difference （P<0.05）. ConclusionIn previously healthy children exposed to infectious influenza cases under unprotected conditions， Xiaoji Hufei formula prophylaxis significantly reduced the incidence of ILI. Xiaoji Hufei Formula can be recommended as a specific preventive prescription for influenza in children.

Objective To construct percutaneous vertebroplasty for predicting osteoporotic vertebral compression fractures(OVCFs)nomogram of residual back pain(RBP)after percutaneous vertebroplasty(PVP).Methods Clinical data of 245 OVCFs patients who were performed PVP from January 2020 to December 2022 were retrospectively analyzed,including 47 males and 198 females,aged from 65 to 77 years old with an average of(71.47±9.03)years old,and were divided into RBP group and non-RBP group according to whether RBP occurred.Gender,age,comorbidities,fracture stage,body mass index(BMI),bone mineral density(BMD),visual analogue scale(VAS),Oswestry disability index(ODI)and other general infor-mation were collected;anterior vertebral height(AVH),anterior vertebral height ratio(AVH),anterior vertebral height ratio(AVHR),Cobb angle,intravertebral vacuum cleft(IVC),thoracolumbar fascia(TLF)injury,paravertebral muscle steatosis,injection volume and leakage of bone cement,bone cement dispersion pattern,anterior vertebral height recovery ratio(AVHRR),Cobb angle changes,etc.imaging parameters before operation and 24 h after operation were collected.Univariate analysis was performed to analysis above factors,and multivariate Logistic regression model was used to investigate indepen-dent risk factors for postoperative RBP,and Nomogram model was constructed and verified;receiver operating characteristic(ROC)curve and calibration curve were used to determine predictive performance and accuracy of the model,and Hosmer-Lemeshow(H-L)test was used for evaluation.The area under curve(AUC)of ROC was calculated,and Harrell consistency index(C index)was used to evaluate the predictive efficiency of model;decision curve analysis(DCA)was used to evaluate clinical practicability of model.Results There were 34 patients in RBP group and 211 patients in non-RBP group.There were no significant differences in gender,age,comorbidities,fracture stage,BMI,BMD,VAS,ODI,AVH,AVHR and Cobb angle be-tween two groups(P＞0.05).Univariate analysis showed 6 patients occurred IVC in RBP group and 13 patients in non-RBP,the number of IVC in RBP group was higher than that in non-RBP group(x2=5.400,P=0.020);6 patients occuured TLF injury in RBP group and 11 patients in non-RBP group,the number of TLF injury in RBP group was higher than that in non-RBP group(x2=7.011,P=0.008);In RBP group,18 patients with grade 3 to 4 paraptebral steatosis and 41 patients in non-RBP group,RBP group was higher than non-RBP group(x2=21.618,P＜0.001),and the proportion of bone cement mass in RBP group was higher than non-RBP group(x2=6.836,P=0.009).Multivariate Logistic regression analysis showed IVC(x2=4.974,P=0.025),TLF in-jury(x2=5.231,P=0.023),Goutallier grade of paravertebral steatosis＞2(x2=15.124,P＜0.001)and proportion of bone cement(x 2=4.168,P=0.038)were independent risk factors for RBP after PVP.ROC curve of model showed AUC of original model was 0.816[OR=2.862,95％CI(0.776,0.894),P＜0.001].The internal verification of model through 200 bootstrap samples showed the value of C index was 0.936,and calibration curve showed predicted probability curve was close to actual probability curve.H-L goodness of fit test results were x2=5.796,P=0.670.DCA analysis results showed the decision curve was above None line and All line when the threshold value ranged from 6％to 71％.Conclusion IVC,TLF combined injury,paravertebral muscle steatosis with Goutallier grade＞2,and bone cement diffusion with mass type are independent risk factors for RBP after PVP.The risk prediction model for RBP after PVP established has good predictive performance and good clinical practicability.