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.

Blood turbidity and collateral disease are closely related to each other as the important component parts of the theoretical system of modern traditional Chinese medicine (TCM). The former focuses on blood and the latter on blood vessels and collaterals. By integrating these two theories, a theoretical basis for TCM syndrome differentiation and treatment of modern diseases can be provided. This article summarizes the correlation of origin, concept, treatment method and representative drugs of two theories, and points out that both blood turbidity and collateral disease prospers and develops through the integration of TCM classical theory and modern medical achievements. Theoretically, blood turbidity is the cause of collateral disease, and collateral disease is the result of aggravated blood turbidity. In many metabolic diseases, blood turbidity and collateral disease actually correspond to the main features of the early and late stages of the same disease, respectively. In treatment, clearing blood turbidity is consistent with dredging collaterals. When clearing blood turbidity, it is necessary to dredge the collaterals, and when dredging the collaterals, it is necessary to clear the blood turbidity. In terms of prescription and medication, Huazhuo Xingxue Decoction is the representative prescription of blood turbidity, which can be combined with Ramulus Cinnamomi, Sichuan lovage rhizome, earthworm, and other dredging collateral drugs. The representative prescription for collateral disease is Tongxinluo Capsule, which can be combined with lotus leaf, Fructus Crataegi, cassia seed, and other turbid-clearing drugs to enhance the curative effect.

Preeclampsia(PE)is a severe pregnancy complication that poses significant risks to maternal and fetal health,and its pathogenesis remains unclear.Recent studies have shown that lactate dehydrogenase(LDH),a key enzyme in glycolysis,plays a piv-otal role in the development and progression of PE.This article reviews the abnormal changes in the levels of LDH and its isozymes in serum and placental tissue and their impact on the pathogenesis of PE and analyzes the molecular mechanisms by which LDH subunits contribute to placental dysfunction through multiple pathways including hypoxia,inflammation,autophagy dysregulation,and cellular damage.In addition,this article discusses the role of lactate,a metabolic product of LDH activity,in the pathogenesis of PE.LDH can be used as a potential biomarker for PE,and the regulation of non-metabolic functions and metabolic reprogramming mediated by LDH provide new targets for the prevention and treatment of PE.

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.

BackgroundAttention deficit hyperactivity disorder （ADHD） is a neurodevelopmental disorder characterized by age-inappropriate inattention， excessive activities incongruous with setting， and emotional impulsivity. Subthreshold ADHD （sADHD） is clinically defined as the presence of ADHD symptoms that do not meet the full diagnostic criteria for ADHD. Children with sADHD exhibit deficits in executive function， demonstrate more conduct， learning， and anxiety-related problems compared to typically developing children， and show even poorer working memory performance than children diagnosed with ADHD. Currently， there is limited epidemiological research on sADHD in China， with few studies simultaneously investigating the prevalence of both ADHD and sADHD in children. ObjectiveTo investigate the prevalence of ADHD and sADHD among children aged 6–13 years in Chongqing， analyzing their distribution characteristics within this population， with the aim of providing references for developing preventive measures against both ADHD and sADHD. MethodsFrom October to November 2023， a total of 3 398 students in grades 1–6 from six primary schools in Jiangbei District， Chongqing were selected using a stratified cluster random sampling method. The occurrence of ADHD and sADHD was evaluated by using the short version （18-item version） of the Swanson， Nolan， and Pelham IV rating scales （SNAP-IV） and the Chinese vision of Schedule for Affective Disorder and Schizophrenia for School-aged Children-Present and Lifetime Version （K-SADS-PL）. ResultsThe ADHD detection rate among children in Chongqing was 1.90% （95% CI： 0.014–0.024）. Boys showed a significantly higher ADHD detection rate than girls （χ²=7.733， P=0.005）. No statistically significant differences were found in ADHD detection rates across different grades or age groups （χ²=7.347， 12.362， P>0.05）. The sADHD detection rate was 6.32% （95% CI： 0.054–0.072）. Similarly， boys exhibited significantly higher sADHD detection rates than girls （χ²=21.005， P<0.01）. Significant differences emerged across different grades （χ²=20.559， P=0.001）， while no statistically significant difference was observed in age groups （χ²=12.070， P=0.060）. ConclusionThe ADHD detection rates were comparable across all grade levels and age groups from 6–13 years old. Second-grade children demonstrated notably higher sADHD rates compared to other grades， while boys demonstrated higher prevalence rates than girls for both ADHD and sADHD. ［Funded by Science and Health Joint Medical Research Project in Jiangbei District， Chongqing City in the Second Half of 2023 （number， 2023JBKWLH022）］

Objective To explore the diagnostic value of brain cord blood flow ultrasound combined with glucose metabolism indexes in the patients with preeclampsia(PE)complicated with fetal growth restriction(FGR).Methods This study was a prospective cohort case-control study.A total of 198 PE patients admitted to the hospital from January 2017 to January 2022 were collected and divided into group A(PE patients com-plicated with FGR,101 cases)and group B(PE patients without FGR,97 cases)according to whether they were complicated with FGR.45 pregnant women with healthy prenatal examination in the hospital were se-lected as group C,and the differences of brain cord blood flow ultrasound indexes and glucose metabolism inde-xes among the three groups and the efficiency for diagnosing PE complicated with FGR were analyzed.Results Fast-ing blood glucose and fasting insulin levels in group A,group B and group C were gradually decreased(P＜0.05).The peak systolic flow velocity/peak diastolic flow velocity(S/D),resistance index(RI)and pulsatility index(PI)of middle cerebral artery(MCA)of fetus in group A,group B and group C increased gradually(P＜0.05).The levels of umbilical artery(UA)of fetus in group A,group B and group C decreased gradually(P＜0.05).The area under the curve of fasting insulin,fasting blood glucose,S/D,RI and PI of MCA,S/D,RI,PI of UA and the combined detection were 0.782,0.748,0.765,0.836,0.805,0.758,0.811,0.795 and 0.895,respectively.The diagnostic efficiency of combined detection was higher than that of single diagnosis(Z=4.327,4.862,4.551,3.400,3.946,4.679,3.742,4.102,P＜0.05).Conclusion The combined detection of glucose metabolism indexes and brain cord blood flow ultrasound indexes is of great value in the differential diagnosis of patients with PE complicated with FGR,and has good clinical application value.

Objective To investigate the influencing factors of vancomycin in the area under curve for 24 h(AUC0-24h)in patients after orthopedic surgery,and to predictive and analyze a good pharmacokinetic model for AUC0-24h Methods Patients who underwent orthopedic surgery and used vancomycin in The Sixth Affiliated Hospital of Xinjiang Medical University from January 2018 to December 2022 were included,and the basic information,the medication,the blood and biochemical indexes of the patients were collected to analyze the factors affecting postoperative vancomycin AUC0-24h in orthopedic surgery.The AUC0-24h was calculated using the first-level pharmacokinetic formula,the JavaPK? for Desktop(JPKD)and the vancomycin daily dose elimination rate formula.Results 91 patients were finally included,and the cystatin C(OR=189.168,P=0.005)and the single dose(OR=19.160,P＜0.001)were independent protective factors for vancomycin AUC0 24 h in postoperative orthopedic patients,and the retinol binding protein was an independent risk factor for vancomycin AUC0-24h(OR=0.910,P＜0.05).By predicting and analyzing the model of vancomycin AUC0 24h in postoperative orthopedic patients,the absolute percentage error of both JPKD software and vancomycin daily dose elimination rate formula were lower than 30％.The intraclass correlation efficient between the AUC0 24h of the JPKD software and vancomycin daily dose elimination rate formula,and the AUC0 24h of the first-level pharmacokinetic formula were 0.781 and 0.524,respectively.Conclusion Cystatin C is an important factor influencing vancomycin AUC0-24h in postoperative orthopedic patients,and JPKD software is more suitable for predicting vancomycin AUC0-24h after orthopedic surgery than the vancomycin daily dose elimination rate formula method.