OBJECTIVE: To summarize the research progress of bioactive scaffolds in the repair and regeneration of osteoporotic bone defects. METHODS: Recent literature on bioactive scaffolds for the repair of osteoporotic bone defects was reviewed to summarize various types of bioactive scaffolds and their associated repair methods. RESULTS: The application of bioactive scaffolds provides a new idea for the repair and regeneration of osteoporotic bone defects. For example, calcium phosphate ceramics scaffolds, hydrogel scaffolds, three-dimensional (3D)-printed biological scaffolds, metal scaffolds, as well as polymer material scaffolds and bone organoids, have all demonstrated good bone repair-promoting effects. However, in the pathological bone microenvironment of osteoporosis, the function of single-material scaffolds to promote bone regeneration is insufficient. Therefore, the design of bioactive scaffolds must consider multiple factors, including material biocompatibility, mechanical properties, bioactivity, bone conductivity, and osteogenic induction. Furthermore, physical and chemical surface modifications, along with advanced biotechnological approaches, can help to improve the osteogenic microenvironment and promote the differentiation of bone cells. CONCLUSION With advancements in technology, the synergistic application of 3D bioprinting, bone organoids technologies, and advanced biotechnologies holds promise for providing more efficient bioactive scaffolds for the repair and regeneration of osteoporotic bone defects.
Humans ; Tissue Scaffolds/chemistry* ; Bone Regeneration ; Osteoporosis/therapy* ; Tissue Engineering/methods* ; Biocompatible Materials/chemistry* ; Printing, Three-Dimensional ; Calcium Phosphates/chemistry* ; Osteogenesis ; Ceramics ; Cell Differentiation ; Hydrogels ; Bioprinting ; Bone and Bones

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

The objectification of facial diagnosis has been developed through recent years and has become a multidisciplinary research topic.However,many studies are still limited to the adjustment of algorithms and the design of data collection environment and equipments,few studies focus on facial diagnosis zoning.The purpose of this paper is to discuss the problems in the current research literature on machine learning-based intelligent TCM facial diagnosis zoning to build a foundation for subsequent related research.The study uses bibliometric methods and text analysis to clarify and analyze the current intelligent TCM facial diagnosis zoning methods,which mainly include facial feature point-based,facial feature block-based and complete face-based method;then by analyzing the influencing factors of facial diagnosis zoning research and summarizing the common machine learning algorithms,the advantages and disadvantages of different machine learning algorithms and the corresponding common facial diagnosis zoning methods are obtained;Finally,we discuss three aspects of the current phase of facial diagnosis zoning research:dataset construction,advantages of deep learning,and embodiment of facial diagnosis theory.

BACKGROUND: Patellofemoral joint (PFJ) degeneration has traditionally been regarded as a contraindication to unicompartmental knee arthroplasty (UKA). More recently, some researchers have proposed that PFJ degeneration can be ignored in medial UKA, and others have proposed that this change should be reviewed in PFJ degenerative facets and severity. This study aimed to systematically evaluate the effect of PFJ degeneration on patient-reported outcome measures (PROMs) and revision rates after medial UKA. METHODS: Electronic databases (PubMed, Embase, Web of Science, etc.) were searched for studies assessing the influence of PFJ degeneration on medial UKA. A random-effects meta-analysis was conducted for the Oxford knee score (OKS), Knee society score (KSS), and revision rates and stratified by PFJ degenerative facets (medial/lateral/trochlear/unspecified), severe PFJ degeneration (bone exposed), and bearing type (mobile/fixed). Heterogeneity was assessed by the Cochran Q test statistic and chi-squared tests with the I-squared statistic. RESULTS: A total of 34 articles with 7007 knees (2267 with PFJ degeneration) were included (5762 mobile-bearing and 1145 fixed-bearing and 100 unspecified). Slight to moderate degenerative changes in the medial and trochlear facets did not decrease the OKS and KSS, and only lateral facets significantly decreased the OKS (mean difference [MD] = -2.18, P   <  0.01) and KSS (MD = -2.61, P   <  0.01). The severity degree of PFJ degeneration had no additional adverse effect on the OKS, KSS, or revision rates. For mobile-bearing UKA, only lateral PFJ degeneration significantly decreased the OKS (MD = -2.21, P  < 0.01) and KSS (MD = -2.44, P  < 0.01). For fixed-bearing UKA, no correlation was found between PROMs/revision rates and PFJ degeneration. CONCLUSION For medial mobile-bearing UKA, slight to moderate degenerative changes in the PFJ, except lateral facet, did not compromise PROMs or revision rates. For medial fixed-bearing UKA, although it might not be conclusive enough, PROMs or revision rates were not adversely affected by PFJ degeneration (regardless of the facet).
Humans ; Arthroplasty, Replacement, Knee ; Patellofemoral Joint/surgery* ; Treatment Outcome ; Osteoarthritis, Knee/surgery* ; Knee Prosthesis ; Bone Diseases ; Knee Joint/surgery* ; Retrospective Studies

BACKGROUND: Despite the advent of innovative knee prosthesis design, a consistent first-option knee implant design in total knee arthroplasty (TKA) remained unsettled. This study aimed to compare the clinical effects among posterior-stabilized (PS), cruciate-retaining (CR), bi-cruciate substituting (BCS), and bi-cruciate retaining designs for primary TKA. METHODS: Electronic databases were systematically searched to identify eligible randomized controlled trials (RCTs) and cohort studies from inception up to July 30, 2021. The primary outcomes were the range of knee motion (ROM), and the secondary outcomes were the patient-reported outcome measures (PROMs) and complication and revision rates. Confidence in evidence was assessed using Confidence in Network Meta-Analysis. The Bayesian network meta-analysis was performed for synthesis. RESULTS: A total of 15 RCTs and 18 cohort studies involving 3520 knees were included. The heterogeneity and inconsistency were acceptable. There was a significant difference in ROM at the early follow-up when PS was compared with CR (mean difference [MD] = 3.17, 95% confidence interval [CI] 0.07, 7.18) and BCS was compared with CR (MD = 9.69, 95% CI 2.18, 17.51). But at the long-term follow-up, there was no significant difference in ROM in any one knee implant compared with the others. No significant increase was found in the PROMs and complication and revision rates at the final follow-up time. CONCLUSIONS At early follow-up after TKA, PS and BCS knee implants significantly outperform the CR knee implant in ROM. But in the long run, the available evidence suggests different knee prostheses could make no difference in clinical outcomes after TKA with extended follow-up.
Humans ; Arthroplasty, Replacement, Knee ; Posterior Cruciate Ligament/surgery* ; Network Meta-Analysis ; Osteoarthritis, Knee/surgery* ; Knee Joint/surgery* ; Knee Prosthesis ; Range of Motion, Articular

OBJECTIVE: To review the research progress of mitochondrial dynamics mediated by optic atrophy 1 (OPA1) in skeletal system diseases. METHODS: The literatures about OPA1-mediated mitochondrial dynamics in recent years were reviewed, and the bioactive ingredients and drugs for the treatment of skeletal system diseases were summarized, which provided a new idea for the treatment of osteoarthritis. RESULTS: OPA1 is a key factor involved in mitochondrial dynamics and energetics and in maintaining the stability of the mitochondrial genome. Accumulating evidence indicates that OPA1-mediated mitochondrial dynamics plays an important role in the regulation of skeletal system diseases such as osteoarthritis, osteoporosis, and osteosarcoma. CONCLUSION OPA1-mediated mitochondrial dynamics provides an important theoretical basis for the prevention and treatment of skeletal system diseases.
Humans ; GTP Phosphohydrolases/genetics* ; Mitochondrial Dynamics ; Osteoarthritis ; Osteoporosis

Osteoarthritis (OA) is a prevalent degenerative joint disease characterized by cartilage loss and accounts for a major source of pain and disability worldwide. However, effective strategies for cartilage repair are lacking, and patients with advanced OA usually need joint replacement. Better comprehending OA pathogenesis may lead to transformative therapeutics. Recently studies have reported that exosomes act as a new means of cell-to-cell communication by delivering multiple bioactive molecules to create a particular microenvironment that tunes cartilage behavior. Specifically, exosome cargos, such as noncoding RNAs (ncRNAs) and proteins, play a crucial role in OA progression by regulating the proliferation, apoptosis, autophagy, and inflammatory response of joint cells, rendering them promising candidates for OA monitoring and treatment. This review systematically summarizes the current insight regarding the biogenesis and function of exosomes and their potential as therapeutic tools targeting cell-to-cell communication in OA, suggesting new realms to improve OA management.
Apoptosis ; Cartilage/pathology* ; Cartilage, Articular/metabolism* ; Cell Communication ; Chondrocytes/metabolism* ; Exosomes/pathology* ; Humans ; Osteoarthritis/therapy*

Background::Although various therapies have been developed to treat malalignment in osteoarthritic knees, the pattern of malalignment progression is still unclear. This study aimed to identify homogeneous subgroups with distinct trajectories of malalignment progression in subjects with symptomatic knee osteoarthritis (KOA) and to determine corresponding risk factors.Methods::Eight-year follow-up (from 2004 to 2012) data on 1252 participants with symptomatic KOA from the Osteoarthritis Initiative were included. Varus/valgus angle progression was characterized by group-based trajectory models. Time-varying covariates were introduced into the model to investigate how they affected trajectories. Multinomial logistic regression for trajectory group membership was applied to ascertain risk factors.Results::Five subgroups were identified. Participants in the varus worsening trajectory ( n = 166) or valgus worsening trajectory ( n = 118) proceeded to worsen malalignment over time. The neutral trajectory ( n = 378), varus stable trajectory ( n = 328), and valgus stable trajectory ( n = 262) maintained close to the initial varus/valgus angle over 8 years. Higher baseline Kellgren and Lawrence grade (odds ratio [OR] = 4.35, P < 0.001 for varus; OR= 3.85, P < 0.001 for valgus) and "severe" baseline malalignment (OR = 13.57, P < 0.001 for varus; OR = 23.04, P < 0.001 for valgus) were risk factors for worsening trajectories. The cutoff point of the baseline varus/valgus angle to discriminate between stable or worsening trajectory was -4.5° for varus and 3.6° for valgus. Conclusions::This study identified the malalignment progression pattern — minor malalignment (-4.5° to +3.6°) tends to remain stable, while major baseline malalignment is likely to progress. This provides a reference for therapy to prevent malalignment from deteriorating and emphasizes the necessity of determining the trigger factors for malalignment onset.

Objective:To explore the effect of combined problem-based learning (PBL) and lecture-based learning (LBL) on the teaching of skeletal motor system diseases for eight-year clinical medicine program students.Methods:The clinical eight-year medical students from Batch 2014 and 2015 participating in the teaching of "osteoarthritis" in the course of Skeletal Motor System Diseases in West China Clinical Medical College of Sichuan University were divided into control group (60 students) and experimental group (82 students). The control group was taught by LBL teaching method, while the experimental group was taught by PBL+LBL teaching method. A questionnaire survey was conducted to retrospectively analyze the teaching effects, including learning enthusiasm, knowledge understanding, thinking ability, teamwork ability, practical ability, self-learning ability and teacher-student relationship, as well as the evaluation of teaching satisfaction. The SPSS 22.0 software was used for t test and chi-square test. Results:The survey results showed that students in the experimental group were significantly superior to those in the control group in such aspects as learning enthusiasm (8.00±1.61 vs. 7.28±1.98), knowledge understanding (8.02±1.59 vs. 7.33±1.79), thinking ability (8.34±1.66 vs. 7.42±1.90), teamwork ability (8.32±1.76 vs. 6.60±2.79), practical ability (7.70±1.69 vs. 6.87 ± 2.57), self-learning ability (8.05±1.65 vs. 7.35±2.48) and teacher-student relationship (7.96±1.75 vs. 7.25±2.10), with statistically significant differences ( P<0.05). Meanwhile, the PBL+LBL group was more satisfied with the teaching mode than the LBL group, and the difference was statistically significant ( P<0.05). Conclusion:The application of PBL+LBL teaching method in clinical medicine eight-year program course teaching of "osteoarthritis" in Skeletal Motor System Diseases can effectively improve the learning enthusiasm of students, improve the quality of education, and obtain good teaching effect.

BACKGROUND: Physical therapy is regarded as an essential aspect in achieving optimal outcomes following total knee arthroplasty (TKA). The coronavirus disease 2019 (COVID-19) pandemic has made face-to-face rehabilitation inaccessible. Virtual reality (VR) is increasingly regarded as a potentially effective option for offering health care interventions. This systematic review and meta-analysis investigate VR-based rehabilitation's effectiveness on outcomes following TKA. METHODS: From inception to May 22, 2021, PubMed/Medline, Embase, Web of Science, the Cochrane Central Register of Controlled Trials, Scopus, PsycINFO, Physiotherapy Evidence Database, China National Knowledge Infrastructure, and Wanfang were comprehensively searched to identify randomized controlled trials (RCTs) evaluating the effect of VR-based rehabilitation on patients following TKA according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement and the Cochrane Handbook for Systematic Reviews of Interventions. RESULTS: Eight studies were included in the systematic review, and seven studies were included in the meta-analysis. VR-based rehabilitation significantly improved visual analog scale (VAS) scores within 1 month (standardized mean difference [SMD]: -0.44; 95% confidence interval [CI]: -0.79 to -0.08, P = 0.02), the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) within 1 month (SMD: -0.71; 95% CI: -1.03 to -0.40, P < 0.01), and the Hospital for Special Surgery Knee Score (HSS) within 1 month and between 2 months and 3 months (MD: 7.62; 95% CI: 5.77 to 9.47, P < 0.01; MD: 10.15; 95% CI: 8.03 to 12.27, P < 0.01; respectively) following TKA compared to conventional rehabilitation. No significant difference was found in terms of the Timed Up and Go (TUG) test. CONCLUSIONS VR-based rehabilitation improved pain and function but not postural control following TKA compared to conventional rehabilitation. More high-quality RCTs are needed to prove the advantage of VR-based rehabilitation. As the COVID-19 pandemic continues, it is necessary to promote this rehabilitation model.
Arthroplasty, Replacement, Knee ; COVID-19 ; Humans ; Randomized Controlled Trials as Topic ; SARS-CoV-2 ; Virtual Reality