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.

Objective: To investigate the correlation among α2, 6-sialyltransferase (ST6Gal-Ⅰ), CD36 desialylation, and caveolin-1 (Cav-1) in phorbol ester (PMA)-induced MEG-01 cell model, as well as their potential mechanism in immune thrombocytopenia (ITP). Methods: MEG-01 cells were treated with 10 ng/mL PMA for 48 hours (control group: 0.1% DMSO). Flow cytometry was used to detect cell surface markers: desialylation (CD41 RCA ) and α2, 6-sialylation (CD41 SNA ). Western blot was performed to analyze the protein expressions of ST6Gal-Ⅰ, CD36, and Cav-1. Results: Flow cytometry analysis revealed that, compared with the control group (set as 100%), the proportion of CD41 RCA positive cells in the MEG-01 cells after PMA intervention significantly increased to (127.79±2.01)%, while the proportion of CD41 SNA positive cells significantly decreased to (78.09±1.76)% (both P<0.05). Western blot analysis results showed that, compared with the control group, PMA intervention significantly downregulated the expression of ST6Gal-Ⅰ protein (0.602±0.023 vs 0.768±0.068) and Cav-1 protein (1.012±0.028 vs 1.253±0.068) (both P<0.05), while significantly upregulating the expression of CD36 protein (0.936±0.033 vs 0.694±0.070, P<0.05). Conclusion: PMA can significantly inhibit the expression of ST6Gal-Ⅰ, accompanied by increased desialylation (β-galactose exposure), elevated CD36, and downregulated Cav-1. These changes suggest that the increased exposure of CD36 antigen and the disorder of membrane microenvironment may be involved in the pathological process of ITP, providing a new direction for mechanism research.

Objective This study aims to investigate the expression, phenotypic changes, and mechanisms of action of guanylate-binding protein 2 (GBP2) in the process of silica-induced pulmonary fibrosis. Methods The expression and localization of GBP2 in silicotic lung tissue were detected by immunohistochemical staining and immunofluorescence. An in vitro cell model was constructed, and methods such as Western blot and real-time quantitative reverse transcription polymerasechain reaction were utilized to investigate the function of GBP2 in different cell lines following silica stimulation. The mechanism of action of GBP2 in various cell lines was elucidated using Western blot analysis. Results GBP2 was highly expressed in the lung tissue of patients with silicosis. Immunohistochemical staining and immunofluorescence have revealed that GBP2 was localized in macrophages and epithelial cells. In vitro cell experiments demonstrated that silicon dioxide stimulated THP-1 cells to activate the c-Jun pathway through GBP2, promoting the secretion of inflammatory factors and facilitating the occurrence of M2 macrophage polarization. In epithelial cells, GBP2 promoted the occurrence of epithelial to mesenchymal transition (EMT) by upregulating Krueppel-like factor 8 (KLF8). Conclusion GBP2 not only activates c-Jun in macrophages to promote the production of inflammatory factors and the occurrence of M2 macrophage polarization, but also activates the transcription factor KLF8 in epithelial cells to induce EMT, collectively promoting the progression of silicosis.
Humans ; Silicosis/genetics* ; Macrophages/cytology* ; Epithelial Cells/pathology* ; GTP-Binding Proteins/physiology* ; Epithelial-Mesenchymal Transition ; Disease Progression ; Cell Line ; Male

Protrusive facial deformities, characterized by the forward displacement of the teeth and/or jaws beyond the normal range, affect a considerable portion of the population. The manifestations and morphological mechanisms of protrusive facial deformities are complex and diverse, requiring orthodontists to possess a high level of theoretical knowledge and practical experience in the relevant orthodontic field. To further optimize the correction of protrusive facial deformities, this consensus proposes that the morphological mechanisms and diagnosis of protrusive facial deformities should be analyzed and judged from multiple dimensions and factors to accurately formulate treatment plans. It emphasizes the use of orthodontic strategies, including jaw growth modification, tooth extraction or non-extraction for anterior teeth retraction, and maxillofacial vertical control. These strategies aim to reduce anterior teeth and lip protrusion, increase chin prominence, harmonize nasolabial and chin-lip relationships, and improve the facial profile of patients with protrusive facial deformities. For severe skeletal protrusive facial deformities, orthodontic-orthognathic combined treatment may be suggested. This consensus summarizes the theoretical knowledge and clinical experience of numerous renowned oral experts nationwide, offering reference strategies for the correction of protrusive facial deformities.
Humans ; Orthodontics, Corrective/methods* ; Consensus ; Malocclusion/therapy* ; Patient Care Planning ; Cephalometry

Lumbar disc (LD) herniation and aging are prevalent conditions that can result in substantial morbidity. This study aimed to clarify the mechanisms connecting the LD aging and herniation, particularly focusing on cellular senescence and molecular alterations in the nucleus pulposus (NP). We performed a detailed analysis of NP samples from a diverse cohort, including individuals of varying ages and those with diagnosed LD herniation. Our methodology combined histological assessments with single-nucleus RNA sequencing to identify phenotypic and molecular changes related to NP aging and herniation. We discovered that cellular senescence and a decrease in nucleus pulposus progenitor cells (NPPCs) are central to both processes. Additionally, we found an age-related increase in NFAT1 expression that promotes NPPC senescence and contributes to both aging and herniation of LD. This research offers fresh insights into LD aging and its associated pathologies, potentially guiding the development of new therapeutic strategies to target the root causes of LD herniation and aging.
Intervertebral Disc Displacement/metabolism* ; Humans ; Aging/pathology* ; Nucleus Pulposus/pathology* ; Male ; Female ; Transcriptome ; Middle Aged ; Lumbar Vertebrae/pathology* ; Adult ; Cellular Senescence ; Stem Cells/pathology* ; Aged ; Intervertebral Disc Degeneration/metabolism*

Objective To construct myeloid-specific Spi1 gene knockout mice and analyze their genotypes,so as to provide animal model basis for the study of pathological mechanism of diseases and drug targets.Methods Ac-cording to the principle of CRISPR/Cas9 technology and Cre/LoxP system,sgRNA and Donor vectors were de-signed and constructed.The transcript of Exon 2(Exon 2)was used as the knockout region,and Loxp elements were placed on both sides of Exon 2.Cas9 protein,sgRNA and Donor vector were mixed and microinjected into the fertilized eggs of C57BL/6J mice,the fertilized eggs were transplanted into the uterus of C57BL/6J pregnant female mice,and F0 generation was obtained after 19～20 days.Positive F0 mice were mated with C57BL/6J mice to ob-tain stable F1 Spi1flox/+mice.Spi1flox/+mice of F1 generation were selfed to obtain Spi1flox/flox mice.Spi1flox/flox mated with Lyz2-Cre+mice to obtain Spi1flox/+/Lyz2-Cre+mice,and then mated with Spi1flox/flox,the Spi1flox/flox/Lyz2-Cre+mice were myeloid-specific Spi1 gene knockout(KO)mice.Spi1flox/flox/Lyz2-cre-mice were used as wild-type(WT)mice.DNA of WT and KO mice was extracted,and the genotypes were identified by agarose gel electro-phoresis after PCR amplification.Western blot was used to detect the expression of spleen focus forming virus provi-ral integration oncogene,Spi-1/purine rich box-1(PU.1)in immune cells of WT and KO mice.Results The results of PCR identification showed that the genotype of mice with only 220 bp amplified by flox primer was Spi1flox/flox homozygote,and the genotype of mice with 700 bp amplified by Lyz2-Cre primer was Lyz2-Cre+.Western blot showed that compared with WT group,the protein PU.1 was not expressed in bone marrow-derived macropha-ges(BMDMs)and peritoneal macrophages(PM)in KO group(P<0.01).There was no significant difference of statistics in the expression level of PU.1 in T cells between KO mice and WT mice.The results of PCR and West-ern blot showed that myeloid-specific Spi1 KO mice were successfully constructed.Conclusion The myeloid-spe-cific Spi1 gene KO mice are successfully constructed and identified,which provides animal model basis for further revealing the potential mechanism of PU.1 inimmune regulation.