Macrophage polarization is involved in the entire process of the occurrence and development of knee osteoarthritis(KO A).By polarizing into distinct functional phenotypes,macrophages play key regulatory roles in the initiation of inflammation,matrix degradation,suppression of cartilage formation,and progression of the disease.The M1-type macrophages secrete numerous pro-inflammatory cytokines to exacerbate the inflammatory responses and promote the destruction of articular cartilage.Conversely,the M2-type macrophages help maintain the extracellular matrix homeostasis and facilitate cartilage formation by releasing anti-inflammatory factors while suppressing the secretion of inflammatory factors,thereby exerting anti-inflammatory effects and promoting tissue repair.Recent studies have shown that an imbalanced ratio of M1/M2 macrophages(M1/M2 ratio)is closely linked with both the pathogenesis and progression of KO A.Restoration of the dynamic balance between these two subtypes could be an essential strategy for treating and preventing KO A.This article reviewed the current literatures retrieved from PubMed and CNKI databases using the keywords"knee osteoarthritis"and"macrophages"over the past decade.The review introduced the process of macrophage polarization and the mechanisms of different macrophage phenotypes in KOA,and further discussed the recent advances in modulating the M1/M2 ratio for KOA management through chemical drugs,bioactive molecules,and traditional Chinese medicine and so on,aiming to provide the theoretical insights for future research and clinical interventions.

Objective:To investigate the structural changes in the spinal cord in multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD) and their relationship with clinical disability.Methods:This study was cross-sectional. A retrospective analysis of clinical and imaging data from 124 patients with MS (MS group), 101 patients with aquaporin-4 antibody-positive NMOSD (NMOSD group), and 110 healthy controls (HC group) from seven medical centers were conducted from January 2018 to October 2021. All subjects underwent 3D T 1WI, and the upper cervical spinal cord cross-sectional area (MUCCA) was segmented and measured. All patients completed the expanded disability status scale (EDSS) assessments at baseline and during follow-up, as well as the baseline 25-foot walk test (T25FW) and the nine-hole peg test (NHPT). Patients were classified into EDSS progression and non-progression groups based on follow-up EDSS scores. Comparisons of MUCCA among the three groups were conducted using analysis of covariance, controlling for age and sex as covariates. Pairwise comparisons between groups were performed using the HSD test. Univariate linear regression and logistic models were employed to identify candidate predictors of baseline clinical disability status or EDSS progression in the MS and NMOSD groups. L1 regularized multivariable linear regression analysis was used to determine independent predictors of baseline clinical disability status or EDSS progression. Independent predictors were then combined to establish a logistic regression model, and the model′s performance in predicting EDSS progression was evaluated using receiver operating characteristic analysis and the area under the curve (AUC). Results:A total of 144 patients completed follow-up EDSS assessments, with a follow-up duration of 3.30 (1.10, 6.42) years, including 82 patients in the MS group and 62 patients in the NMOSD group. Controlling for sex and age as covariates, the overall difference in MUCCA among the MS, NMOSD, and HC groups was statistically significant ( P=0.001). The MUCCA in the MS group was lower than that in the HC group, with a significant difference ( t=-2.54, P=0.007); the MUCCA in the NMOSD group was also lower than that in the HC group, with a significant difference ( t=-2.80, P=0.002). However, the difference in MUCCA between the MS and NMOSD groups was not statistically significant ( t=-0.40, P=0.882). In the MS group, MUCCA was an independent predictor of baseline EDSS score (β=-0.03), baseline T25FW score (β=-0.09), and baseline NHPT score (β=-0.30). In the NMOSD group, MUCCA (β=-0.08), age (β=0.06), and baseline EDSS score (β=-0.43) were independent predictors of EDSS progression, and the logistic regression model incorporating these three factors predicted EDSS progression with an AUC of 0.82. Conclusions:Significant spinal cord atrophy occurs in patients with both MS and NMOSD. Atrophy of the upper cervical spinal cord can predict the degree of disability in MS patients and the progression of clinical disability in NMOSD patients.

Objective:To investigate the structural changes in the spinal cord in multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD) and their relationship with clinical disability.Methods:This study was cross-sectional. A retrospective analysis of clinical and imaging data from 124 patients with MS (MS group), 101 patients with aquaporin-4 antibody-positive NMOSD (NMOSD group), and 110 healthy controls (HC group) from seven medical centers were conducted from January 2018 to October 2021. All subjects underwent 3D T 1WI, and the upper cervical spinal cord cross-sectional area (MUCCA) was segmented and measured. All patients completed the expanded disability status scale (EDSS) assessments at baseline and during follow-up, as well as the baseline 25-foot walk test (T25FW) and the nine-hole peg test (NHPT). Patients were classified into EDSS progression and non-progression groups based on follow-up EDSS scores. Comparisons of MUCCA among the three groups were conducted using analysis of covariance, controlling for age and sex as covariates. Pairwise comparisons between groups were performed using the HSD test. Univariate linear regression and logistic models were employed to identify candidate predictors of baseline clinical disability status or EDSS progression in the MS and NMOSD groups. L1 regularized multivariable linear regression analysis was used to determine independent predictors of baseline clinical disability status or EDSS progression. Independent predictors were then combined to establish a logistic regression model, and the model′s performance in predicting EDSS progression was evaluated using receiver operating characteristic analysis and the area under the curve (AUC). Results:A total of 144 patients completed follow-up EDSS assessments, with a follow-up duration of 3.30 (1.10, 6.42) years, including 82 patients in the MS group and 62 patients in the NMOSD group. Controlling for sex and age as covariates, the overall difference in MUCCA among the MS, NMOSD, and HC groups was statistically significant ( P=0.001). The MUCCA in the MS group was lower than that in the HC group, with a significant difference ( t=-2.54, P=0.007); the MUCCA in the NMOSD group was also lower than that in the HC group, with a significant difference ( t=-2.80, P=0.002). However, the difference in MUCCA between the MS and NMOSD groups was not statistically significant ( t=-0.40, P=0.882). In the MS group, MUCCA was an independent predictor of baseline EDSS score (β=-0.03), baseline T25FW score (β=-0.09), and baseline NHPT score (β=-0.30). In the NMOSD group, MUCCA (β=-0.08), age (β=0.06), and baseline EDSS score (β=-0.43) were independent predictors of EDSS progression, and the logistic regression model incorporating these three factors predicted EDSS progression with an AUC of 0.82. Conclusions:Significant spinal cord atrophy occurs in patients with both MS and NMOSD. Atrophy of the upper cervical spinal cord can predict the degree of disability in MS patients and the progression of clinical disability in NMOSD patients.

Objective:To investigate the feasibility and clinical diagnostic value of rapid arterial spin labeling (ASL) imaging in brain glioma.Methods:Patients with glioma admitted to Beijing Tiantan Hospital, Capital Medical University from May 2021 to December 2022 were prospectively enrolled. All patients received MR rapid ASL (scan time: 1 min) and conventional ASL (scan time: 4 min 30 s), where the cerebral blood flow (CBF) perfusion maps were obtained. The qualitative analysis of CBF signal intensity and quantitative analysis of average CBF values from both tumor solid and edema regions were conducted by two radiologists independently. Kappa test and intraclass correlation coefficient ( ICC) were used to analyze the consistency of qualitative and quantitative results, respectively. Results:A total of 30 patients with brain glioma were included. The 2 physicians used rapid ASL to determine low perfusion, isoperfusion, and hyperperfusion in the tumor area in 1, 6, 23 cases and 0, 5, and 25 cases, respectively; and used conventional ASL to determine low perfusion, isoperfusion, and hyperperfusion in the tumor area in 0, 9, and 21 cases, respectively. The results of qualitative analysis of rapid ASL and conventional ASL were highly consistent within and between groups ( Kappa was 0.830 and 0.850 respectively). The results of quantitative analysis of rapid ASL and conventional ASL were highly consistent within and between groups ( ICC 0.940—0.994). Conclusion:Rapid ASL with shorter scanning time could be applied in assessing tissue perfusion in brain glioma and contribute to the clinical diagnosis of gliomas.

Objective:To construct a spatial radiomics model based on the spatial distribution characteristics of supratentorial pilocytic astrocytoma (PA) and ganglioglioma (GG) and to evaluate its differential diagnosis efficiency.Methods:The study was a cross-sectional study. A retrospective collection of 244 patients with episodic PA and GG who attended Beijing Tiantan Hospital of Capital Medical University (Center 1) from June 2016 to June 2022 and 116 patients with episodic PA and GG who attended General Hospital of Eastern Theater Command (Center 2) from March 2019 to October 2022 was performed. The patients in Center 1 were divided into a training set (171 patients) and a validation set (73 patients) in a 7∶3 ratio according to the random number table method, and the patients in Center 2 as a whole were regarded as test sets. All patients underwent MRI. Segmentation of tumor based on enhanced T 1WI and T 2WI images, alignment to standard space to generate a statistical parametric mapping of tumor locations and intergroup comparison was conducted. The Johns Hopkins University template was used to extract 189 tumor location features to construct a spatial model of tumor location; PyRadiomic 3.0.1 software was used to extract tumor radiomics features to construct a radiomics model; and the two models were fused to construct a spatial radiomics model. The efficacy of spatial radiomics model, spatial model, and radiomics model to discriminate PA from GG was analyzed using receiver operating characteristic curves and area under the curve (AUC). The generalization ability of the model was assessed by the difference in accuracy between the test sets and the validation sets (ΔACC). The clinical utility of the model was compared using clinical decision curves and calibration curves. Results:The statistical parametric mapping of lesions showed that supratentorial PA was vulnerable to medial structure areas such as suprasellar region, thalamus, basal ganglia and frontal lobe, temporal lobe, parietal lobe. GG was mainly distributed in bilateral temporal lobes, as well as frontal lobe, occipital lobe and parietal lobe. The AUCs of spatial radiomics model, radiomics model and spatial model to identify PA and GG in the test set were 0.876, 0.785, and 0.819, with accuracies of 77.59%, 72.41%, and 77.14%, respectively, and ΔACCs in the test set and validation set were 11.6%, 15.43%, and 6.94%, respectively. The clinical decision curves showed an overall greater clinical benefit of the spatial radiomics model compared with the conventional radiomics model and spatial model.Conclusion:Spatial radiomics model containing spatial information on lesion location can improve the diagnostic efficacy of supratentorial PA and GG, and enhance the generalization of the prediction model.

Background::Few evidence is available in the early prediction models of behavioral and psychological symptoms of dementia (BPSD) in Alzheimer’s disease (AD). This study aimed to develop and validate a novel genetic-clinical-radiological nomogram for evaluating BPSD in patients with AD and explore its underlying nutritional mechanism.Methods::This retrospective study included 165 patients with AD from the Chinese Imaging, Biomarkers, and Lifestyle (CIBL) cohort between June 1, 2021, and March 31, 2022. Data on demographics, neuropsychological assessments, single-nucleotide polymorphisms of AD risk genes, and regional brain volumes were collected. A multivariate logistic regression model identified BPSD-associated factors, for subsequently constructing a diagnostic nomogram. This nomogram was internally validated through 1000-bootstrap resampling and externally validated using a time-series split based on the CIBL cohort data between June 1, 2022, and February 1, 2023. Area under receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were used to assess the discrimination, calibration, and clinical applicability of the nomogram.Results::Factors independently associated with BPSD were: CETP rs1800775 (odds ratio [OR] = 4.137, 95% confidence interval [CI]: 1.276-13.415, P = 0.018), decreased Mini Nutritional Assessment score (OR = 0.187, 95% CI: 0.086-0.405, P <0.001), increased caregiver burden inventory score (OR = 8.993, 95% CI: 3.830-21.119, P <0.001), and decreased brain stem volume (OR = 0.006, 95% CI: 0.001-0.191, P = 0.004). These variables were incorporated into the nomogram. The area under the ROC curve was 0.925 (95% CI: 0.884-0.967, P <0.001) in the internal validation and 0.791 (95% CI: 0.686-0.895, P <0.001) in the external validation. The calibration plots showed favorable consistency between the prediction of nomogram and actual observations, and the DCA showed that the model was clinically useful in both validations. Conclusion::A novel nomogram was established and validated based on lipid metabolism-related genes, nutritional status, and brain stem volumes, which may allow patients with AD to benefit from early triage and more intensive monitoring of BPSD.Registration::Chictr.org.cn, ChiCTR2100049131.

This article summarizes and organizes relevant publications in journals, along with a review of medical history, systematically summarizing the development process of dental alveolar surgery in China. The initial establishment phase (1935—1952) marked the starting point of Chinese Alveolar Surgery. Despite the impact of wars, it laid the foundation for subsequent research and practice. During the early development phase (1953—1966), the "Chinese Journal of Stomatology" was founded, which promoted the development of Alveolar Surgery. Research focused on tooth extraction methods and complications. Tooth Transplantation and Preprosthetic Surgery gradually began to take off. The stagnant phase (1967—1977) occurred due to the interruption of international exchanges, leading to an almost complete halt in the development of Alveolar Surgery. Entering the rapid catch-up phase (1978—1985), Alveolar Surgery scholars in China began striving to overcome the stagnation of the previous decade. While some progress was made, no significant innovative achievements emerged. In the scientific development phase (1986—2010), clinical research, basic experiments, and paper writing in modern Chinese Alveolar Surgery began to adhere to scientific standards with the rise of experimental medicine. The exploration and innovation stage (2011—2023) is the current development phase, during which Chinese Aveolar Surgery has reached its peak, making substantial progress in technology, clinical practices, and basic research, gradually reaching or even surpassing international advanced levels. Looking back at the development history in China, we can find the wisdom and hard work of the older generation of Alveolar Surgery scholars. However, contemporary challenges and issues, such as standardizing technology, promoting clinical practices, and talent cultivation, need to be addressed by present-day Alveolar Surgery professionals as they forge ahead.

Objective:To evaluate the long-term efficacy of laparoscopic-assisted natural orifice specimen extraction surgery (NOSES) colectomy using Cai tube for treating left-sided colorectal cancer.Methods:This was a randomized controlled trial. Inclusion criteria were as follows: preoperative pathological diagnosis of left-sided colorectal adenocarcinoma (rectal, sigmoid colon, descending colon, or left transverse colon cancer with the caudad margin ≥8 cm from the anal margin); preoperative abdominal and pelvic computed tomography (or magnetic resonance imaging) showing maximum tumor diameter <4.5 cm; and BMI <30 kg/m 2. Patients with synchronous multiple primary cancers or recurrent cancers, a history of neoadjuvant chemoradiotherapy, preoperative evidence of significant local infiltration, distant metastasis, or complications such as intestinal obstruction and intestinal perforation, or who were not otherwise considered suitable for laparoscopic surgery were excluded. A random number table was used to randomize sequential patients to NOSES surgery using Cai tube (non-assisted incision anal sleeve: patent number ZL201410168748.2) (NOSES group) or traditional laparoscopic-assisted surgery (CLS group). Relevant clinical data of the two groups of patients were analyzed, the main outcomes being disease-free survival, overall survival, overall recurrence rate, and local recurrence rate 5 years after surgery. Results:Patients in both study groups completed the surgery successfully with no requirement for additional surgery. After mean 70 (7–83) months postoperative follow-up, the 5-year overall postoperative survival in the NOSES and CLS groups was 90.0% and 83.3%, respectively ( P=0.455); disease free survival was 90.0% and 83.3%, respectively ( P=0.455); overall recurrence rate 6.6% and 10.0%, respectively ( P=0.625); and local recurrence rate both were 3.3% ( P=0.990), respectively. None of these differences was statistically significant. Conclusions:NOSES and CLS have similar long-term efficacy, and NOSES deserves to be used in clinical practice.

Objective:To evaluate the long-term efficacy of laparoscopic-assisted natural orifice specimen extraction surgery (NOSES) colectomy using Cai tube for treating left-sided colorectal cancer.Methods:This was a randomized controlled trial. Inclusion criteria were as follows: preoperative pathological diagnosis of left-sided colorectal adenocarcinoma (rectal, sigmoid colon, descending colon, or left transverse colon cancer with the caudad margin ≥8 cm from the anal margin); preoperative abdominal and pelvic computed tomography (or magnetic resonance imaging) showing maximum tumor diameter <4.5 cm; and BMI <30 kg/m 2. Patients with synchronous multiple primary cancers or recurrent cancers, a history of neoadjuvant chemoradiotherapy, preoperative evidence of significant local infiltration, distant metastasis, or complications such as intestinal obstruction and intestinal perforation, or who were not otherwise considered suitable for laparoscopic surgery were excluded. A random number table was used to randomize sequential patients to NOSES surgery using Cai tube (non-assisted incision anal sleeve: patent number ZL201410168748.2) (NOSES group) or traditional laparoscopic-assisted surgery (CLS group). Relevant clinical data of the two groups of patients were analyzed, the main outcomes being disease-free survival, overall survival, overall recurrence rate, and local recurrence rate 5 years after surgery. Results:Patients in both study groups completed the surgery successfully with no requirement for additional surgery. After mean 70 (7–83) months postoperative follow-up, the 5-year overall postoperative survival in the NOSES and CLS groups was 90.0% and 83.3%, respectively ( P=0.455); disease free survival was 90.0% and 83.3%, respectively ( P=0.455); overall recurrence rate 6.6% and 10.0%, respectively ( P=0.625); and local recurrence rate both were 3.3% ( P=0.990), respectively. None of these differences was statistically significant. Conclusions:NOSES and CLS have similar long-term efficacy, and NOSES deserves to be used in clinical practice.

Objective:To investigate the efficacy of a machine learning model based on radiomics of brain lesions on T 2WI in differentiating multiple sclerosis (MS) from neuromyelitis optica spectrum disorders (NMOSD). Methods:Totally 223 MS and NMOSD patients who were treated from January 2009 to September 2018 in Beijing Tiantan Hospital Affiliated to Capital Medical University, Donghu Branch of the First Affiliated Hospital of Nanchang University, Tianjin Medical University General Hospital, and Xuanwu Hospital of Capital Medical University were analyzed retrospectively, and according to the proportion of 7∶3, 223 patients were completely randomly divided into training set (156 cases) and test set (67 cases). A total of 74 patients with MS and NMOSD who were treated in Huashan Hospital Affiliated to Fudan University and China-Japan Friendship Hospital of Jilin University from January 2009 to September 2018 and in Xianghu Branch of the First Affiliated Hospital of Nanchang University from March 2020 to September 2021 were collected as an independent external validation set. All patients underwent brain cross-sectional MR T 2WI, radiomics features were extracted from T 2WI, and features were selected by max-relevance and min-redundancy and least absolute shrinkage and selection operator algorithms. Then various machine learning classifier models (logistic regression, decision tree, AdaBoost, random forest or support vector machine) were constructed to differentiate MS from NMOSD. The area under curve (AUC) of receiver operating characteristics was used to evaluate the performance of each classifier model in the training set, test set and external validation set. Results:Based on multi-center T 2WI, a total of 11 radiomics features related to the discrimination between MS and NMOSD were extracted and classifier models were constructed. Among them, the random forest model had the best efficiency in distinguishing MS from NMOSD, and its AUC values for distinguishing MS from NMOSD in the training set, test set and external validation set were 1.000, 0.944 and 0.902, with specificity of 100%, 76.9% and 86.0%, and sensitivity of 100%, 92.1% and 79.7%, respectively. Conclusion:The random forest model based on the radiomic features of T 2WI of brain lesions can effectively distinguish MS from NMOSD.