BACKGROUND:The number of patients receiving total knee arthroplasty has been increasing globally each year.Pain management is a crucial aspect following total knee arthroplasty,as effective pain control can facilitate early mobilization,reduce complications,enhance patient satisfaction,and accelerate the rehabilitation process.OBJECTIVE:To construct a visual map of post-total knee arthroplasty pain,understand the international research status and trends in this field,and provide a reference for future studies.METHODS:Relevant research articles on post-total knee arthroplasty pain were retrieved from the CNKI,WanFang Data,and Web of Science core databases,covering the period from January 2000 to December 2023.The CiteSpace software(version 6.2.3)was used to analyze the annual publication output,authors,institutions,countries,keywords,and references.Utilizing R programming language(version 4.4.1),a database was established to create line charts and bar graphs.RESULTS AND CONCLUSION:(1)Our analysis included 3 796 publications,predominantly in Chinese(3 509 articles)with the remainder in English(287 articles).(2)The United States was the most productive country in English literature,with Harvard University leading institutional output.Guangzhou University of Chinese Medicine was the top publishing institution in Chinese literature.(3)Keyword clustering identified"quality of life,""phobia,"and"acupuncture"as emerging focal points in Chinese literature,while"satisfaction"and"psychological factors"were prominent in English literature over the past five years.Co-occurrence and clustering analysis revealed dense internal connections among institutions,authors,and publications,but sparse external collaborations.(4)The study's bias on visualization analysis may have introduced bias by excluding less influential papers.(5)Regarding research hotspots,domestic research emphasized the efficacy and exploration of analgesic methods,in contrast to international research that focused on pain mechanism subtyping and analgesic drug innovation.Future research is expected to trend towards traditional Chinese medicine for postoperative pain,multimodal analgesia,and the investigation and prevention of pain typing mechanisms.

BACKGROUND:The number of patients receiving total knee arthroplasty has been increasing globally each year.Pain management is a crucial aspect following total knee arthroplasty,as effective pain control can facilitate early mobilization,reduce complications,enhance patient satisfaction,and accelerate the rehabilitation process.OBJECTIVE:To construct a visual map of post-total knee arthroplasty pain,understand the international research status and trends in this field,and provide a reference for future studies.METHODS:Relevant research articles on post-total knee arthroplasty pain were retrieved from the CNKI,WanFang Data,and Web of Science core databases,covering the period from January 2000 to December 2023.The CiteSpace software(version 6.2.3)was used to analyze the annual publication output,authors,institutions,countries,keywords,and references.Utilizing R programming language(version 4.4.1),a database was established to create line charts and bar graphs.RESULTS AND CONCLUSION:(1)Our analysis included 3 796 publications,predominantly in Chinese(3 509 articles)with the remainder in English(287 articles).(2)The United States was the most productive country in English literature,with Harvard University leading institutional output.Guangzhou University of Chinese Medicine was the top publishing institution in Chinese literature.(3)Keyword clustering identified"quality of life,""phobia,"and"acupuncture"as emerging focal points in Chinese literature,while"satisfaction"and"psychological factors"were prominent in English literature over the past five years.Co-occurrence and clustering analysis revealed dense internal connections among institutions,authors,and publications,but sparse external collaborations.(4)The study's bias on visualization analysis may have introduced bias by excluding less influential papers.(5)Regarding research hotspots,domestic research emphasized the efficacy and exploration of analgesic methods,in contrast to international research that focused on pain mechanism subtyping and analgesic drug innovation.Future research is expected to trend towards traditional Chinese medicine for postoperative pain,multimodal analgesia,and the investigation and prevention of pain typing mechanisms.

Ferroptosis exhibits a clear “double-edged sword” effect in liver fibrosis， with its impact strictly dependent on the type of target cells. In hepatocytes， ferroptosis induced by specific signaling pathways （such as glutathione peroxidase 4 inhibition） is a key factor for driving hepatic injury and initiating fibrogenesis， and dying hepatocytes activate hepatic stellate cells by releasing damage-associated molecules； on the contrary， in activated hepatic stellate cells， ferroptosis becomes a therapeutic target for promoting liver fibrosis regression， and selective elimination can be achieved by disrupting their distinctive antioxidant defense mechanisms. Moreover， ferroptosis modulates the dynamic balance of the fibrotic liver microenvironment by regulating macrophage polarization and intercellular communication. Based on the above mechanisms， targeting ferroptosis has emerged as a promising strategy for precise treatment. This article summarizes related research advances and discusses the major challenges and future directions for clinical translation.

Objective: To constructCSF1R+/-mice and to analyze their genotypes, so as to provide animal model basis for disease pathological mechanism and drug target. Methods : A linearized targeting vector was designed according to Cre/Loxp system. A Loxp site was inserted upstream of the 5th exon of theCSF1Rgene, and a neomycin resistance box with Loxp sites on both sides was inserted downstream of the 5th exon. The linearized targeting vector was electroporated into embryonic stem cells. The correctly targeted embryonic stem cells were injected into the blastocysts of C57BL/6J mice to obtain chimeric mice, which were bred with Zp3-Cre mice. The newborn mice were numbered 9-14 days after birth and their tails were cut. The DNA of the mice was extracted, and the genotype of the mice was identified by polymerase chain reaction and agarose gel electrophoresis. The expression of CSF1R in mouse macrophages was detected by flow cytometry. The expression of CSF1R in mouse tissues was detected by Western blot. Results: The results of agarose gel electrophoresis showed that 453 bp bands were amplified in wild type mice, and 453 bp and 650 bp bands were amplified in heterozygous mice. The results of flow cytometry showed that the expression of CSF1R in peritoneal macrophages and bone marrow-derived macrophages of CSF1R heterozygous mice was lower than that of WT group(P<0.05). The results of Western blot showed that the expression of CSF1R in spleen, kidney and brain tissue of CSF1R heterozygous group was lower than that of WT group(P<0.05). Conclusion CSF1R+/-mice are successfully constructed, reproduced and identified, which provides an animal model basis for further revealing the potential mechanism of CSF1R in immune regulation.

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.
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Extracellular Traps/immunology* ; Humans ; Lung Neoplasms/metabolism* ; Neutrophils/metabolism* ; Animals ; Tumor Microenvironment

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.

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.