Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

ObjectiveTo explore the effect and mechanism of modified Dingjingtang in regulating the Toll-like receptor 2 （TLR2）/nuclear factor （NF）-κB/NOD-like receptor protein 3 （NLRP3） signaling pathway to inhibit inflammatory skin lesions in the rat model of acne. MethodsForty-eight rats were randomized into the normal， model， low-， medium-， and high-dose （8.1， 16.2， and 32.4 g·kg^-1） modified Dingjingtang， and doxycycline hydrochloride （0.27 g·kg^-1） groups， with 8 rats in each group. Rats in other groups except the normal group were modeled by intradermal injection and intraperitoneal injection of Propionibacterium acnes. After successful modeling， rats in the intervention groups were treated with corresponding agents by gavage， and those in the normal and model groups with an equal volume of normal saline， once a day for 14 consecutive days. Then， the samples were collected. The general conditions， ear thickness， and body weight changes of rats were observed. Biochemical methods were used to determine superoxide dismutase （SOD） and malondialdehyde （MDA） levels in the ear tissue. Hematoxylin-eosin staining and Masson's staining were used to observe the pathological changes and collagen deposition， respectively， in the ear tissue. Immunohistochemistry was employed to determine the interleukin （IL）-1β level in the ear tissue. Enzyme-linked immunosorbent assay was adopted to measure the levels of IL-1β， tumor necrosis factor （TNF）-α， and IL-6 in the serum. The total antioxidant capacity method was adopted to assess the reactive oxygen species （ROS） content in the ear tissue. Western blot and real-time fluorescence quantitative polymerase chain reaction were employed to determine the protein and mRNA levels， respectively， of TLR2， myeloid differentiation factor 88 （MyD88）， NF-κB， NLRP3， and cysteinyl aspartate-specific proteinase-1 （Caspase-1） in the ear tissue. ResultsCompared with the normal group， the model group had increased ear skin thickness （P<0.01）， elevated ROS and MDA levels （P<0.01）， reduced SOD content （P<0.05）， and increased collagen deposition （P<0.01） in the ear tissue. In addition， the model group showed raised IL-1β， IL-6， and TNF-α levels in the serum （P<0.01） and up-regulated mRNA and protein levels of TLR2， MyD88， NF-κB， NLRP3， and Caspase-1 （P<0.01）. Compared with the model group， the high- and medium-dose modified Dingjingtang groups showed significant improving effects regarding the above indicators （P<0.05， P<0.01）. ConclusionModified Dingjingtang can ameliorate the inflammatory skin lesions in the rat model of acne by regulating the TLR2/NF-κB/NLRP3 signaling pathway.

Objective: To investigate the impact of milk and egg supplementation on body composition and bone mineral density of rural primary school students in Yunnan Province, so as to provide a reference for developing targeted nutritional intervention strategies. Methods: In December 2023, a cluster sampling method was adopted to select students from grades one to three in four primary schools each from Jinggu and Shidian countys of Yunnan Province, as the intervention group (662 students). Additionally, two boarding primary schools were selected from each county based on the principle of matching scale and student numbers as the control group (455 students). Starting from April 2023, the intervention group received 200 mL milk and 50 g eggs during the break on school days for 8 months, while the control group maintained their usual diet behavior. Body composition was measured by using bioelectrical impedance analysis, and distal radial bone mineral density was assessed via dual energy X-ray absorptiometry in April and December 2023. The intervention effects were analyzed by using a difference in-differences approach. Results: The final measurements of body fat percentage, skeletal muscle mass and fat free mass of the intervention group and the control group of primary school students were significantly higher than the baseline values, and the net effect of milk and egg intervention on these body composition indicators was not statistically significant ( P >0.05, both before and after adjustment). In contrast, bone mineral density increased significantly by 0.02 g/cm 2 in the intervention group. The net intervention effect on bone mineral density was statistically significant ( β=0.02, 95%CI =0.00-0.04), and remained significant after model adjustment ( β=0.02, 95%CI =0.00-0.04) (both P < 0.05). Subgroup analysis showed statistically significant effects of the intervention among girls ( β=0.02, 95%CI =0.00-0.04), day students ( β=0.04, 95%CI =0.01-0.07), and students with normal nutritional status ( β=0.02, 95%CI =0.00-0.04) (all P <0.05). No significant effect of milk and egg supplementation was observed on body composition indicators (all P <0.05). Conclusions Milk and egg supplementation can improve bone mineral density among rural primary school students in Yunnan Province. It is recommended that rural school aged children should increase intake of milk and eggs to support growth and development.

Objective:To explore the correlation between subclavian artery stenosis disease (SASD) classification and posterior circulation ischemia.Methods:A retrospective study was performed; the clinical data, and Doppler vascular ultrasound and vascular imaging results of 81 SASD patients, admitted to Cerebrovascular Stenosis Diagnosis and Treatment Center, Second Affiliated Hospital of Qiqihar Medical College and Department of Neurology, Rocket Force Specialty Medical Center from May 2018 to August 2023, were collected. SASD was categorized into 2 types (single type and concurrent type) based on the presence or absence of other posterior circulation artery (basilar artery, vertebral artery, or subclavian artery distal segment) stenosis/occlusion, and into 3 groups (non-posterior circulation ischemia group, posterior circulation transient ischemic attack group and posterior circulation cerebral infarction group) based on the presence or absence of posterior circulation ischemia. Blood stealing pathways in different SASD classifications were analyzed, and correlation of SASD classification with posterior circulation ischemia was discussed.Results:Single-type SASD was noted in 44 patients (54.3%), mainly initiating blood stealing through the vertebral artery to the vertebral artery and then to the subclavian artery ( n=26); concurrent-type SASD was noted in 37 patients (45.7%), mainly initiating blood stealing through the occipital artery to the costocervical trunk and then to the subclavian artery ( n=10). Sixty-five patients (80.2%) were into the non-posterior circulation ischemia group, 4 (4.9%) into the posterior circulation transient ischemic attack group and 12 (14.8%) into the posterior circulation cerebral infarction group. Among the 44 patients with single-type SASD, 39 did not have posterior circulation ischemia, and 3 had posterior circulation cerebral infarction. Among the 37 patients with concurrent-type SASD, 26 did not have posterior circulation ischemia, and 9 had posterior circulation cerebral infarction. Conclusion:Initiation of blood stealing in SASD patients is related to SASD classification, and concurrent-type SASD patients trend to have posterior circulation ischemia.

Objective:To establish a scoring system for preoperative prediction of the malignant potential of gastric stromal tumors based on gastroscopic and endoscopic ultrasound features, along with validation.Methods:A total of 286 patients who were treated in Jiangsu Province Hospital of Chinese Medicine from January 1, 2017 to December 31, 2023 and diagnosed as having gastric stromal tumors by postoperative pathology were enrolled in the modeling group. According to National Institutes of Health classification system, 227 very-low/low-risk patients were classified into the low malignant potential (LMP) group, and the 59 intermediate/high-risk patients into the high malignant potential (HMP) group. LASSO regression analysis was performed to identify predictive factors for HMP gastric stromal tumors, and a nomogram prediction model was developed. Internal validation using the Bootstrap method was performed on the modeling group, and external validation was performed on data from 85 patients who were treated and diagnosed as having gastric stromal tumors by postoperative pathology in Taizhou People's Hospital from January 1, 2021 to December 31, 2023. The receiver operator characteristic (ROC) curves, calibration curves, and decision curve analyses were employed in both the modeling and external validation groups.Results:Tumor size (coef=0.755), tumor shape (coef=0.015), tumor location (coef=0.008), growth pattern (coef=-0.026), cystic change (coef=0.685), and surface unceration change (coef=-0.545) were the independent predictive factors for HMP gastric stromal tumors. The nomogram-based prediction model constructed using these factors achieved an area under the ROC curve of 0.959 (95% CI: 0.898-0.903) in the modeling group and 0.959 (95% CI: 0.857-1.000) in the external validation group. The model demonstrated good accuracy (0.917) and a Kappa value of 0.737 in internal validation. Calibration curve and decision curve analyses indicated strong calibration and high net benefit in both the modeling and the external validation groups. Conclusion:Tumor size, tumor shape, tumor location, growth pattern, cystic change, and surface ulceration change are independent predictive factors for HMP gastric stromal tumors. The nomogram model developed based on these factors offers effective and convenient visualization for clinicians to predict the malignant potential of gastric stromal tumors preoperatively.

Background and Objective Accurate diagnosis of mucous cystic lesion(PCL)remains a clinical difficult.Both Carcinoembryonic antigen(CEA)and glucose(GLU)are reported to have ability to distinguish mucinous PCL from non-mucinous PCL,but the accuracy was limited.The objective of this study was to evaluate the value of cystic CEA combined with GLU in the diagnosis of mucinous PCL.Methods PCL patients who underwent pancreatic surgery and endoscopic ultrasonography guided fine-needle aspiration(EUS-FNA)were retrospectively collected from the First Affiliated Hospital of Naval Medical University.Clinical data and cystic fluid analysis of included PCLs patients were analyzed using receiver operator(ROC)curves.ROC analysis,sensitivity and specificity analyses were used to evaluate the value of CEA combined with GLU in the diagnosis of mucinous PCL.Results From January 2015 to December 2021,a total of 84 patients underwent cyst fluid CEA and GLU analysis,of whom 44(52.4％)had mucinous PCL and 40(47.6％)had non-mucinous PCL.The AUC for distinguishing mucinous from non-mucinous PCL by CEA was 0.82[(95％confidence interval(CI):0.72-0.92)].When 192 ng/mL was used as the cutoff level,the diagnostic sensitivity and specificity were 50％and 93％,respectively.Using 20 ng/mL as cutoff level,the diagnostic sensitivity increased to 80％and the specificity decreased to 68％.The AUC for the cystic GLU to distinguish mucinous from non-mucinous PCL was 0.73(95％CI:0.99-0.87),and the diagnostic sensitivity and specificity were 100％and 60％,respectively.When the cutoff level of CEA was 192 ng/mL,the AUC of CEA combined with GLU in the diagnosis of mucinous PCLs was 0.94(95％Cl:0.86-0.99),while when the cutoff level of CEA was 20 ng/mL,the AUC of CEA combined with Glu in the diagnosis of mucinous PCLs was 0.94(95％CI:0.85-0.99).The AUCs were significantly higher than the AUC with single diagnostic indicators.Conclusion When using the cutoff level of 192 ng/mL,cyst fluid CEA combined with GLU has high sensitivity and specificity in differentiating mucinous PCL from non-mucinous PCL,so it can be considered for clinical application.Lower CEA cutoff level(20 ng/mL)can improve the sensitivity of diagnosis.