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.

Neutrophil extracellular traps (NETs), intricate reticular structures released by activated neutrophils, play a pivotal regulatory role in the pathogenesis of malignant tumors. Lung cancer is one of the most prevalent malignancies globally, with persistently high incidence and mortality rates. Recent studies have revealed that NETs dynamically modulate the tumor microenvironment through unique pathological mechanisms, exhibiting complex immunoregulatory characteristics during the progression of lung cancer, and this discovery has increasingly become a focal point in tumor immunology research. This paper provides a comprehensive review of the latest advancements in NETs research related to lung cancer, offering an in-depth analysis of their impact on lung cancer progression, their potential diagnostic value, and the current state of research on targeting NETs for lung cancer prevention and treatment. The aim is to propose novel strategies to enhance therapeutic outcomes and improve the prognosis for lung cancer patients.
.
Extracellular Traps/immunology* ; Humans ; Lung Neoplasms/metabolism* ; Neutrophils/metabolism* ; Animals ; Tumor Microenvironment

ObjectiveTo validate the efficacy of Yunpi Huatan Tongqiao prescription （YHTP） in down-regulating glycolysis to modulate microglia phenotype and improve inflammation and cognitive memory deficits in obstructive sleep apnea （OSA） mice. MethodForty-eight male Balb/C mice were randomly divided into a normal group， a model group， a montelukast sodium group （30 mg·kg^-1）， and low， medium， and high dose groups of YHTP （8.28， 16.56， and 33.12 g·kg^-1）， with 8 mice in each group. All groups， except the normal group， received intraperitoneal injections of lipopolysaccharide （LPS） and underwent chronic intermittent hypoxia （CIH） modeling for 4 weeks. Subsequently， the mice were treated with medications for 4 weeks and then sampled. Animal behavioral tests assessed memory impairment due to hypoxia. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to measure mRNA expression levels of M1-associated inflammatory factors interleukin-1β （IL-1β）， tumor necrosis factor-α （TNF-α）， and markers such as T lymphocyte activation antigen （CD86） and inducible nitric oxide synthase （iNOS）， as well as M2-associated inflammatory factors interleukin-10 （IL-10）， transforming growth factor-β （TGF-β）， and the marker mannose receptor （CD206） in hippocampal tissue. Western blot was employed to detect differences in the expression of M1 and M2 microglia phenotypic markers （CD86， CD206） and glycolysis-related proteins glucose transporter type 1 （GLUT1）， hexokinase 2 （HK2）， phosphofructokinase （PFKM）， pyruvate kinase 2 （PKM2）， and monocarboxylic acid transporter 1 （MCT1）. ResultBehavioral tests showed that compared to the results in the normal group， the Y-maze autonomous alternation rate was significantly reduced in the model group （P<0.01）. The latency time for the target hole in the Barnes' maze during the training period （days 2， 3， 4） and testing period （days 5， 12） was significantly increased （P<0.05， P<0.01）. M1 glial cell markers CD86 and iNOS， as well as inflammatory factors IL-1β and TNF-α mRNA， were significantly elevated （P<0.01）. In contrast， the mRNA expression of M2 glial cell markers IL-10， CD206， and TGF-β was significantly reduced （P<0.01）. The protein expression of glycolytic proteins HK2， PFKM， PKM2， MCT1， and the M1 marker CD86 was significantly increased （P<0.05， P<0.01）， while M2 marker CD206 protein expression was significantly decreased （P<0.01）. Compared to the results in the model group， the Y-maze autonomous alternation rate was significantly increased in the medium and high dose groups of YHTP （P<0.05， P<0.01）. The latency time for the target hole during the training （day 4） and testing periods （days 5， 12） was significantly reduced （P<0.01）. Real-time PCR results indicated that mRNA expression levels of M1-related pro-inflammatory factors in the hippocampal tissue were significantly reduced in the low， medium， and high dose groups of YHTP （P<0.01）， while M2-related inflammatory factors' mRNA expression was significantly increased （P<0.01）. Western blot results showed that in the medium and high dose groups of YHTP， the expression of the M1 marker CD86 in the hippocampus was reduced， whereas the expression of the M2 marker CD206 was significantly increased （P<0.01）， with a significant decrease in the expression of glycolysis-related proteins （P<0.01）. ConclusionYHTP can improve inflammation and cognitive impairment induced by hypoxia in OSA model mice. This is achieved by downregulating glycolysis in brain microglia， inhibiting M1 activation， reducing pro-inflammatory factor release， and promoting M2 activation， thereby exerting a therapeutic effect on inflammation and cognitive impairment caused by OSA.

Objective:To analyze the current situation and influencing factors of family economic burden in children with congeni-tal heart disease,and provide reference basis for relevant departments.Methods:Conduct a questionnaire survey on the parents of children with congenital heart disease,and use a multiple linear regression model to analyze the factors affecting the economic bur-den of the disease.Results:The median total economic burden of families with congenital heart disease is 44 140 yuan,which is higher than the average level of per capita disposable income among residents of Xinjiang from 2020-2022.The median direct non-medical economic burden is 2 700 yuan,and the median indirect economic burden is 2 890 yuan.The length of hospital stay and monthly household income are important factors affecting the total economic burden.Conclusion:The total economic burden of families with congenital heart disease is higher than the per capita disposable income.The more complex the condition,the longer the days of hospitalization and the longer the time lost from work,resulting in a higher overall financial burden.

Lung cancer has the highest incidence and mortality rate among all cancers in China， with its complex and variable nature， long treatment duration， and often poor prognosis. Currently， the treatment of lung cancer mainly employs classical therapies such as surgery， radiotherapy， and chemotherapy， but some patients may experience a series of adverse reactions， which affect their quality of life， survival period， and treatment outcomes. As reported， oxidative stress is one of the important pathogenic factors of lung cancer， affecting its occurrence and development. Oxidative stress is a state of imbalance between oxidative products and antioxidant defense mechanisms in the body. The intervention of oxidative stress in the occurrence and development of lung cancer is related to multiple signaling pathways， including the Kelch-like ECH-associated protein 1 （Keap1）-nuclear factor erythroid 2-related factor 2 （Nrf2） signaling pathway， phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt）/mammalian target of rapamycin （mTOR） signaling pathway， mitogen-activated protein kinase （MAPK） signaling pathway， and nuclear factor-κB （NF-κB） signaling pathway. Currently， researchers in China and abroad have conducted extensive studies on the occurrence and development of lung cancer and the pathophysiological mechanisms of drug intervention. The results have shown that oxidative stress plays an important role in the occurrence and development of lung cancer. Chinese medicine monomers and compounds can regulate oxidative stress levels and intervene in related signaling pathways， thereby inhibiting or delaying the occurrence and development of lung cancer. Based on this， this article mainly summarized the relevant signaling pathways regulating oxidative stress intervention in lung cancer in recent years， and also reviewed the latest research on Chinese medicine monomers and compounds in regulating oxidative stress to treat lung cancer， aiming to provide new ideas for research on drug treatment of lung cancer and clinical drug development， as well as to provide references and guidance for further in-depth mechanistic studies in the future.

Background and purpose:Gastric-type endocervical adenocarcinoma(G-EAC)is a rare variant of endocervical adenocarcinoma,characterized by atypical clinical manifestations and elusive lesions.Due to these factors,G-EAC is prone to being missed or misdiagnosed,significantly impacting the prognosis.Lobular endocervical glandular hyperplasia(LEGH)and atypical LEGH(aLEGH)are considered to be precancerous lesions of G-EAC.These conditions also present overlapping clinical,pathologic and imaging manifestations,making it challenging to differentiate between them preoperatively.The purpose of this study was to investigate the correlation between magnetic resonance imaging(MRI)findings of cystic-solid lesions in the cervix and their underlying pathology in order to enhance the accuracy of distinguishing between LEGH and G-EAC,ultimately aiding in the early diagnosis and appropriate management of these conditions.Methods:Clinical,imaging and pathological data of 37 LEGH and 53 G-EAC patients who attended the Obstetrics and Gynecology Hospital of Fudan University from July 2016 to August 2023 were collected.Analysis was conducted using Pearson Chi-square χ2,Fisher's exact tests and so on.Multivariate analyses were performed using logistic regression.Receiver operating characteristic(ROC)curves were used for performance evaluation.Results:In this study,differences in age,symptoms,extent,size,composition,degree of enhancement,cervical stromal ring,endometrium invasion,pelvic lymph nodes enlargement,and hydrohystera were statistically significant between the two groups(P＜0.05).In the LEGH and aLEGH groups,lesions were primarily localized to the epithelial layer of the endocervical canal.These lesions were predominantly simple cystic(32/37),and the cystic walls often displayed significant enhancement(31/37).In contrast,the G-EAC group presented with lesions involving the myometrium of the uterine cervix(42/53).These lesions were characterized by a solid component in the majority of cases(52/53),a tendency for the disappearance of the cervical stromal ring(46/53).Logistic regression analysis revealed that among the MRI features,lesion composition(OR=50.064)and incomplete cervical stromal ring(OR=40.180)were significant predictors for G-EAC.ROC analysis,incorporating lesion size,composition,enhancement degree,cervical stromal ring,and endometrial involvement,yielded an area under curve(AUC)of 0.970(95%CI:0.931-1.008).Conclusion:Combining multiple MRI features of cystic-solid lesions in the cervix aids in distinguishing between LEGH and G-EAC.