OBJECTIVE: To explore, identify, and develop novel blood-based indicators using machine learning algorithms for accurate preoperative assessment and effective prediction of postoperative complication risks in patients with rheumatoid arthritis (RA) undergoing total knee arthroplasty (TKA). METHODS: A retrospective cohort study was conducted including RA patients who underwent unilateral TKA between January 2019 and December 2024. Inpatient and 30-day postoperative outpatient follow-up data were collected. Six machine learning algorithms, including decision tree, random forest, logistic regression, support vector machine, extreme gradient boosting, and light gradient boosting machine, were used to construct predictive models. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), F1-score, accuracy, precision, and recall. SHapley Additive exPlanations (SHAP) values were employed to interpret and rank the importance of individual variables. RESULTS: According to the inclusion criteria, a total of 1 548 patients were enrolled. Ultimately, 18 preoperative indicators were identified as effective predictive features, and 8 postoperative complications were defined as prediction labels for inclusion in the study. Within 30 days after surgery, 453 patients (29.2%) developed one or more complications. Considering overall accuracy, precision, recall, and F1-score, the random forest model [AUC=0.930, 95% CI (0.910, 0.950)] and the extreme gradient boosting model [AUC=0.909, 95% CI (0.880, 0.938)] demonstrated the best predictive performance. SHAP analysis revealed that anti-cyclic citrullinated peptide antibody, C-reactive protein, rheumatoid factor, interleukin-6, body mass index, age, and smoking status made significant contributions to the overall prediction of postoperative complications. CONCLUSION Machine learning-based models enable accurate prediction of postoperative complication risks among RA patients undergoing TKA. Inflammatory and immune-related blood biomarkers, such as anti-cyclic citrullinated peptide antibody, C-reactive protein, and rheumatoid factor, interleukin-6, play key predictive roles, highlighting their potential value in perioperative risk stratification and individualized management.
Humans ; Arthroplasty, Replacement, Knee/adverse effects* ; Arthritis, Rheumatoid/blood* ; Machine Learning ; Postoperative Complications/blood* ; Female ; Male ; Retrospective Studies ; Middle Aged ; Aged ; Risk Factors ; Preoperative Period ; C-Reactive Protein/analysis* ; Risk Assessment

Corticotomy is a clinical procedure to accelerate orthodontic tooth movement characterized by the regional acceleratory phenomenon (RAP). Despite its therapeutic effects, the surgical risk and unclear mechanism hamper the clinical application. Numerous evidences support macrophages as the key immune cells during bone remodeling. Our study discovered that the monocyte-derived macrophages primarily exhibited a pro-inflammatory phenotype that dominated bone remodeling in corticotomy by CX3CR1^CreERT2; R26^GFP lineage tracing system. Fluorescence staining, flow cytometry analysis, and western blot determined the significantly enhanced expression of binding immunoglobulin protein (BiP) and emphasized the activation of sensor activating transcription factor 6 (ATF6) in macrophages. Then, we verified that macrophage specific ATF6 deletion (ATF6^f/f; CX3CR1^CreERT2 mice) decreased the proportion of pro-inflammatory macrophages and therefore blocked the acceleration effect of corticotomy. In contrast, macrophage ATF6 overexpression exaggerated the acceleration of orthodontic tooth movement. In vitro experiments also proved that higher proportion of pro-inflammatory macrophages was positively correlated with higher expression of ATF6. At the mechanism level, RNA-seq and CUT&Tag analysis demonstrated that ATF6 modulated the macrophage-orchestrated inflammation through interacting with Tnfα promotor and augmenting its transcription. Additionally, molecular docking simulation and dual-luciferase reporter system indicated the possible binding sites outside of the traditional endoplasmic reticulum-stress response element (ERSE). Taken together, ATF6 may aggravate orthodontic bone remodeling by promoting Tnfα transcription in macrophages, suggesting that ATF6 may represent a promising therapeutic target for non-invasive accelerated orthodontics.
Animals ; Mice ; Macrophages/metabolism* ; Tumor Necrosis Factor-alpha/genetics* ; Tooth Movement Techniques/methods* ; Activating Transcription Factor 6/metabolism* ; Bone Remodeling ; Flow Cytometry ; Blotting, Western

Objective To explore the differences in neural activity between patients with anorexia nervosa(AN)and healthy controls(HC),as well as the association between these differences and symptoms in AN patients,using activation likelihood estimation(ALE)meta-analysis.Methods The literature search covered the period from 2000 to March 2025.From a pool of 588 identified studies,4 studies focusing on the neural activity differences between AN patients and HC were selected for inclusion.These studies comprised 106 participants and 21 sets of coordinates.The ALE meta-analysis method was employed,and the GingerALE software was used to systematically analyze the reported brain region changes and their peak coordinates,aiming to investigate the differences in brain functional activity between AN patients and HC.Results Compared to the HC group,AN group showed significantly enhanced activation in the left parahippocampal gyrus/amygdala(ALE value=0.39×10-2),right parahippocampal gyrus/amygdala(ALE value=0.39×10-2)and suboccipital gyrus(ALE value=0.39×10-2),along with a significant reduction in activation in Brodmann area 17(ALE value=0.61×10-2)(P<0.01,FWE corrected).Conclusion Key brain regions in AN patients including the parahippocampal gyrus,inferior occipital gyrus,and amygdala demonstrate significant functional activation abnormalities.

OBJECTIVE To establish management index system for rational drug use of key monitoring drugs， and provide reference for the management of key monitoring drugs in the hospitals. METHODS First， the management index system for rational drug use of key monitoring drugs was drafted by collecting the evidence from related medical literature. Next， using a modified Delphi method， twenty experienced experts from the fields of pharmacy， medical practice， healthcare insurance， and finance were selected to participate in two rounds of questionnaire consultations. Based on the expert enthusiasm coefficient， authority coefficient， degree of opinion concentration， and degree of coordination， the final indicators were determined to establish a management index system for rational drug use of key monitored drugs in medical institutions. RESULTS The expert enthusiasm coefficients reached 100% in both rounds of consultation. In first-level， second-level and third-level indicators， the authority coefficients of experts were 0.89， 0.86 and 0.87， and coordination coefficients of the experts in importance score were 0.300 （P＜ 0.05）， 0.125 （P＜0.05） and 0.139 （P＜0.05）， respectively. The average score for the importance of all indicators reached over 3.5， in which the full score ratio ranged from 35% to 100%. Except that the variation coefficient of a third-level indicator “number of specifications purchased for key monitored drugs” was 0.26， the variation coefficients of rest indicators were less than or equal to 0.25. Based on the results of expert consultation， final version of the management index system established in this study， including two first-level indicators （drug procurement and use， and rational drug use）， five second-level indicators （such as the accessibility， cost-effectiveness） and twenty third-level indicators （such as the number of specifications purchased for key monitored drugs， the increase in the cost of key monitored drugs）. CONCLUSIONS The management index system established in this study possesses high reliability and strong operability， and may provide a reference for the management of key monitoring drugs in the hospitals.

BACKGROUND: Over 20 million colonoscopies are performed in China annually. An automatic clinical decision support system (CDSS) with accurate semantic recognition of colonoscopy reports and guideline-based is helpful to relieve the increasing medical burden and standardize the healthcare. In this study, the CDSS was built under a hierarchical-label interpretable classification framework, trained by a state-of-the-art transformer-based model, and validated in a multi-center style. METHODS: We conducted stratified sampling on a previously established dataset containing 302,965 electronic colonoscopy reports with pathology, identified 2041 patients' records representative of overall features, and randomly divided into the training and testing sets (7:3). A total of five main labels and 22 sublabels were applied to annotate each record on a network platform, and the data were trained respectively by three pre-training models on Chinese corpus website, including bidirectional encoder representations from transformers (BERT)-base-Chinese (BC), the BERT-wwm-ext-Chinese (BWEC), and ernie-3.0-base-zh (E3BZ). The performance of trained models was subsequently compared with a randomly initialized model, and the preferred model was selected. Model fine-tuning was applied to further enhance the capacity. The system was validated in five other hospitals with 3177 consecutive colonoscopy cases. RESULTS: The E3BZ pre-trained model exhibited the best performance, with a 90.18% accuracy and a 69.14% Macro-F1 score overall. The model achieved 100% accuracy in identifying cancer cases and 99.16% for normal cases. In external validation, the model exhibited favorable consistency and good performance among five hospitals. CONCLUSIONS The novel CDSS possesses high-level semantic recognition of colonoscopy reports, provides appropriate recommendations, and holds the potential to be a powerful tool for physicians and patients. The hierarchical multi-label strategy and pre-training method should be amendable to manage more medical text in the future.
Humans ; Colonoscopy/methods* ; Deep Learning ; Decision Support Systems, Clinical ; Female ; Male

To address the problem of data silos in dental specialties caused by equipment heterogeneity, this study developed an Intelligent Internet of Things (IoT)-enabled dental chair platform (hereinafter referred to as the intelligent platform) based on the concept of medical-engineering integration. The platform adopts a three-tier chair-domain interconnection architecture: the bottom tier integrates multi-source sensors and standardized interfaces for automated data acquisition and linkage with hospital information systems; the middle tier provides clinic-level management and remote teaching collaboration; and the top tier employs a blockchain-based secure cloud database for resource allocation and data management. Clinical validation at The Affiliated Stomatological Hospital of Nanjing Medical University demonstrated that, compared with a control group from the same period in 2023, the trial group achieved a 38.0% increase in average daily patient visits (80.6±6.8 vs. 58.4±5.2, t=15.16, P<0.001), a 24.6% reduction in average treatment time [(36.1±6.3) min vs. (47.9±8.5) min, t=7.72, P<0.001], a 39.2% reduction in waiting time [23.3 (16.5, 30.1) min vs. 38.3 (28.3, 48.3) min, U=32.00, P<0.001], a 30.4% reduction in equipment idle rate [8.7% (5.1%, 12.3%) vs. 12.5% (7.4%, 17.6%), U=251.00, P=0.003], and an increase in patient satisfaction from 88.2% (1 519/1 723) to 94.3% (2 186/2 318) ( t=7.26, P<0.001). User research confirmed that the functions most favored by clinicians and patients were "dental chair parameter updating and clinical data integration" [74.7% (80/107)] and "chairside display of diagnostic images" [76.8% (119/155)], respectively. Looking forward, the intelligent platform has the potential to integrate artificial intelligence-assisted diagnosis and 5G-enabled multicenter collaboration to further expand its clinical applications and accelerate the digital transformation of dental healthcare.

Objective To explore the effects of cerium-doped mesoporous bioactive glass nanoparticles(Ce-MBGNs)as reactive oxy-gen species(ROS)-responsive nanocarriers on inflammation in pulp and their potential to promote odontogenic differentiation of dental pulp stem cells(DPSCs).Methods The cytotoxicity of Ce-MBGNs was assessed by CCK-8.The expression of mRNA of osteogenic/odontogenic differentiation in DPSCs and that of inflammatory factor in RAW264.7 cells were detected by RT-qPCR.Alkaline phospha-tase and Alizarin Red S staining were utilized to investigate their ability to promote dentin mineralization.The ability of Ce-MBGNs to scavenge ROS was evaluated by immunofluorescence and JC-1 staining was used to assess the membrane potential(MMP)of mitochon-drial.Results Ce-MBGNs exhibited good biocompatibility and significantly increased the expression of osteogenic/odontogenic-related genes in DPSCs,promoting mineralization.Additionally,Ce-MBGNs effectively scavenged intracellular ROS,maintained MMP,inhib-ited the expression of pro-inflammatory factors,and promoted the expression of anti-inflammatory factors.Conclusion Ce-MBGNs can protect DPSCs from oxidative damage by maintaining the MMP of mitochondrial and controlling inflammation,and promote their odonto-blastic differentiation,providing a theoretical basis for the development of novel therapeutic agents for oral treatment.

Objective To compare the safety and efficacy of various brachial plexus block techniques using local anesthesia(LA)in patients undergoing their first radiocephalic arteriovenous fistula(RCAVF)surgery.Methods Patients were randomly allocated into three groups:LA,interscalene brachial plexus block(ISBPB),and axillary brachial plexus block(ABPB).Ultrasound was utilized to evaluate the pre-and post-anesthesia changes in vessel diameter and blood flow.Postoperative follow-up assessments were performed at three days and three months to determine fistula patency.Results Immediate patency rates were 92.52％(LA),96.26％(ISBPB),and 95.33％(ABPB),with no statistically significant differences among the groups(χ2=1.615,P=0.446).However,at three months,primary patency rates differed significantly among the groups(χ2=22.691,P<0.001).Specifically,the ISBPB group(83.18％)exhibited significantly higher patency compared to the LA group(57.01％)(χ2=17.477,P<0.001).Similarly,the ABPB group(80.37％)demonstrated better patency than the LA group(χ2=13.580,P<0.001).Regarding respiratory complications,they were more prevalent in the ISBPB group(15.89％)compared to the LA group(2.80％)(χ2=9.761,P=0.002)and the ABPB group(0.93％)(χ2=14.377,P<0.001).No significant difference was observed between the LA and ABPB groups in terms of respiratory complications(χ2=1.019,P=0.313).Conclusions Both ISBPB and ABPB demonstrated superior primary patency compared to LA.Nevertheless,ABPB exerted a lesser impact on respiratory function and provided a more comfortable surgical experience for ESRD patients.

To address the problem of data silos in dental specialties caused by equipment heterogeneity, this study developed an Intelligent Internet of Things (IoT)-enabled dental chair platform (hereinafter referred to as the intelligent platform) based on the concept of medical-engineering integration. The platform adopts a three-tier chair-domain interconnection architecture: the bottom tier integrates multi-source sensors and standardized interfaces for automated data acquisition and linkage with hospital information systems; the middle tier provides clinic-level management and remote teaching collaboration; and the top tier employs a blockchain-based secure cloud database for resource allocation and data management. Clinical validation at The Affiliated Stomatological Hospital of Nanjing Medical University demonstrated that, compared with a control group from the same period in 2023, the trial group achieved a 38.0% increase in average daily patient visits (80.6±6.8 vs. 58.4±5.2, t=15.16, P<0.001), a 24.6% reduction in average treatment time [(36.1±6.3) min vs. (47.9±8.5) min, t=7.72, P<0.001], a 39.2% reduction in waiting time [23.3 (16.5, 30.1) min vs. 38.3 (28.3, 48.3) min, U=32.00, P<0.001], a 30.4% reduction in equipment idle rate [8.7% (5.1%, 12.3%) vs. 12.5% (7.4%, 17.6%), U=251.00, P=0.003], and an increase in patient satisfaction from 88.2% (1 519/1 723) to 94.3% (2 186/2 318) ( t=7.26, P<0.001). User research confirmed that the functions most favored by clinicians and patients were "dental chair parameter updating and clinical data integration" [74.7% (80/107)] and "chairside display of diagnostic images" [76.8% (119/155)], respectively. Looking forward, the intelligent platform has the potential to integrate artificial intelligence-assisted diagnosis and 5G-enabled multicenter collaboration to further expand its clinical applications and accelerate the digital transformation of dental healthcare.

Objective To explore the effects of cerium-doped mesoporous bioactive glass nanoparticles(Ce-MBGNs)as reactive oxy-gen species(ROS)-responsive nanocarriers on inflammation in pulp and their potential to promote odontogenic differentiation of dental pulp stem cells(DPSCs).Methods The cytotoxicity of Ce-MBGNs was assessed by CCK-8.The expression of mRNA of osteogenic/odontogenic differentiation in DPSCs and that of inflammatory factor in RAW264.7 cells were detected by RT-qPCR.Alkaline phospha-tase and Alizarin Red S staining were utilized to investigate their ability to promote dentin mineralization.The ability of Ce-MBGNs to scavenge ROS was evaluated by immunofluorescence and JC-1 staining was used to assess the membrane potential(MMP)of mitochon-drial.Results Ce-MBGNs exhibited good biocompatibility and significantly increased the expression of osteogenic/odontogenic-related genes in DPSCs,promoting mineralization.Additionally,Ce-MBGNs effectively scavenged intracellular ROS,maintained MMP,inhib-ited the expression of pro-inflammatory factors,and promoted the expression of anti-inflammatory factors.Conclusion Ce-MBGNs can protect DPSCs from oxidative damage by maintaining the MMP of mitochondrial and controlling inflammation,and promote their odonto-blastic differentiation,providing a theoretical basis for the development of novel therapeutic agents for oral treatment.