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

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.

Purpose To investigate the expression of chromogranin A(CgA)in gastroenteropancreatic neuroendo-crine neoplasms(GEP-NENs)and its relationship with clinicopathological features.Methods The clinicopathological data of GEP-NENs diagnosed in the Department of Pathology,Beijing Chao-yang Hospital,Capital Medical University from May 2011 to December 2024 were retrospectively analyzed.Immunohistochemical staining was applied to evaluate the expression of CgA,and the patients were divided into CgA(+)group and CgA(-)group.Differences in clinico-pathological features between the 2 groups were compared.Results The age of 229 patients ranged from 21 to 89 years,with an average age of 54.4 years.The most common primary site was the rectum(56.8％,130/229),fol-lowed by the stomach(16.6％,38/229),pancreas(14.4％,33/229),small intestine(6.1％,14/229),and colon(6.1％,14/229).There were 206 cases of single lesion and 23 cases of multiple lesions(number of tumors ≥2).There were 153 cases of G1(66.8％),29 cases of G2(12.7％),7 cases of G3(3.1％),and 40 cases of neuroendocrine carcinoma(NEC,17.5％).The positive rates of CgA in G1,G2,G3,and NEC groups were 37.2％,75.8％,71.4％,and 65.0％,respectively,with statistically significant differences(P＜0.001).The positive rates of CgA in T1,T2,T3,and T4 were 37.2％,83.3％,75.9％,and 57.7％,respectively,with statistically significant differences(P＜0.001).There were significant differences in age,vascular invasion,lymph node metasta-sis,and number of tumors between CgA(+)group and CgA(-)group(P＜0.001),but there was no significant difference in sex,tumor location,Syn,and CD56 expression between the two groups(P=0.595,P=0.098,P=0.173,P=0.557).Conclusion Immunohistochemical antibody CgA is a useful marker for GEP-NENs.CgA positiv-ity may be a poor prognostic factor for GEP-NENs patients.

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.

Purpose To investigate the expression of chromogranin A(CgA)in gastroenteropancreatic neuroendo-crine neoplasms(GEP-NENs)and its relationship with clinicopathological features.Methods The clinicopathological data of GEP-NENs diagnosed in the Department of Pathology,Beijing Chao-yang Hospital,Capital Medical University from May 2011 to December 2024 were retrospectively analyzed.Immunohistochemical staining was applied to evaluate the expression of CgA,and the patients were divided into CgA(+)group and CgA(-)group.Differences in clinico-pathological features between the 2 groups were compared.Results The age of 229 patients ranged from 21 to 89 years,with an average age of 54.4 years.The most common primary site was the rectum(56.8％,130/229),fol-lowed by the stomach(16.6％,38/229),pancreas(14.4％,33/229),small intestine(6.1％,14/229),and colon(6.1％,14/229).There were 206 cases of single lesion and 23 cases of multiple lesions(number of tumors ≥2).There were 153 cases of G1(66.8％),29 cases of G2(12.7％),7 cases of G3(3.1％),and 40 cases of neuroendocrine carcinoma(NEC,17.5％).The positive rates of CgA in G1,G2,G3,and NEC groups were 37.2％,75.8％,71.4％,and 65.0％,respectively,with statistically significant differences(P＜0.001).The positive rates of CgA in T1,T2,T3,and T4 were 37.2％,83.3％,75.9％,and 57.7％,respectively,with statistically significant differences(P＜0.001).There were significant differences in age,vascular invasion,lymph node metasta-sis,and number of tumors between CgA(+)group and CgA(-)group(P＜0.001),but there was no significant difference in sex,tumor location,Syn,and CD56 expression between the two groups(P=0.595,P=0.098,P=0.173,P=0.557).Conclusion Immunohistochemical antibody CgA is a useful marker for GEP-NENs.CgA positiv-ity may be a poor prognostic factor for GEP-NENs patients.

Interleukin-1 receptor-related kinase (IRAK4) is a widely expressed serine/threonine kinase involved in the regulation of innate immunity. IRAK4 plays a pivotal role as a key kinase within the downstream signaling pathway cascades of interleukin-1 receptors (IL-1R) and Toll-like receptors (TLRs). The signaling pathways orchestrated by IRAK4 are integral to inflammatory responses, and its overexpression is implicated in the pathogenesis of inflammatory diseases, autoimmune disorders, and cancer. Consequently, targeting IRAK4-mediated signaling pathways has emerged as a promising therapeutic strategy. Small molecule inhibitors and degraders designed to modulate IRAK4 have shown efficacy in mitigating related diseases. In this paper, we will provide a detailed description of the structure and function of IRAK4, the role of IRAK4 in related diseases, as well as the currently reported small molecule inhibitors and degraders of IRAK4. It is expected to provide new directions for enriching the clinical treatment of inflammation and related diseases.