BACKGROUND:Bone tissue loss caused by tumors and trauma can have an adverse effect on postoperative rehabilitation.Therefore,scaffold materials are usually implanted during treatment.However,the existing implant materials are relatively simple and lack antibacterial properties.Early implantation may lead to iatrogenic autoinfection and have an adverse effect on osteogenesis.OBJECTIVE:To construct a KR-12-a5 polypeptide-nanohydroxyapatite-small intestinal submucosa composite scaffold and evaluate its feasibility as a material for promoting bone defect repair.METHODS:The small intestinal submucosa scaffold and the small intestinal submucosa scaffold containing 25,50,and 100 mg/mL nanohydroxyapatite(referred to as nHA-SIS scaffold)were prepared by 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride/N-hydroxysuccinimide cross-linking method.The appropriate scaffold was screened for subsequent experiments by mechanical property testing.The antibacterial properties of KR-12-a5 polypeptide solution against Staphylococcus aureus,Streptococcus gordonii,and Fusobacterium nucleatum were detected.The nHA-SIS scaffolds were immersed in 250,500,and 1 000 μg/mL KR-12-a5 peptide solutions for 24 hours,and then freeze-dried to obtain peptide-loaded nanohydroxyapatite-porcine small intestinal submucosa composite scaffolds(denoted as P-nHA-SIS scaffolds).The sustained-release properties of the three groups of scaffolds were characterized.The nHA-SIS scaffolds and the three groups of P-nHA-SIS scaffolds were co-cultured with Staphylococcus aureus,Streptococcus gordonii,and Fusobacterium nucleatum for 24 hours or 48 hours.The scaffolds with strong antibacterial ability were screened by live and dead bacteria staining and scanning electron microscopy for subsequent experiments.The degradation properties and water absorption rates of the uncross-linked small intestinal submucosa scaffolds,cross-linked small intestinal submucosa scaffolds,nHA-SIS scaffolds,and P-nHA-SIS scaffolds were characterized.The extracts of cross-linked small intestinal submucosal scaffolds,nHA-SIS scaffolds,and P-nHA-SIS scaffolds were co-cultured with MC3T3-E1 cells.CCK-8 assay and live-dead cell staining were performed.The effects of the extracts of the three scaffolds on the migration of MC3T3-E1 cells were detected by Transwell chamber assay.RESULTS AND CONCLUSION:(1)The elastic modulus and compressive strength of 25,50,and 100 mg/mL nHA-SIS scaffolds were higher than those of small intestinal submucosal scaffolds(P＜0.05),among which the elastic modulus and compressive strength of 25 mg/mL nHA-SIS scaffolds were the highest,and this group of scaffolds were selected for subsequent experiments to load peptides.(2)KR-12-a5 peptide had strong antibacterial activity against common bacteria in bone defects(Staphylococcus aureus,Streptococcus gordonii,and Fusobacterium nucleatum).The three groups of P-nHA-SIS scaffolds all had sustained release properties.With the increase of peptide mass concentration,the antibacterial property of P-nHA-SIS scaffold was enhanced.Among them,the P-nHA-SIS scaffold loaded with 500 μg/mL peptide had achieved a satisfactory antibacterial effect,and this group of scaffolds would be selected in the future.(3)The degradation rate of the three groups of cross-linked scaffolds was lower than that of the uncross-linked scaffolds,and the water absorption rate was greater than that of the uncross-linked scaffolds.P-nHA-SIS scaffolds could promote the proliferation and migration of MC3T3-E1 cells without affecting the activity of MC3T3-E1 cells.(4)The results show that P-nHA-SIS scaffolds have strong antibacterial properties and the ability to promote the proliferation and migration of MC3T3-E1 cells,and are expected to be used in bone defect repair.

BACKGROUND:Bone tissue loss caused by tumors and trauma can have an adverse effect on postoperative rehabilitation.Therefore,scaffold materials are usually implanted during treatment.However,the existing implant materials are relatively simple and lack antibacterial properties.Early implantation may lead to iatrogenic autoinfection and have an adverse effect on osteogenesis.OBJECTIVE:To construct a KR-12-a5 polypeptide-nanohydroxyapatite-small intestinal submucosa composite scaffold and evaluate its feasibility as a material for promoting bone defect repair.METHODS:The small intestinal submucosa scaffold and the small intestinal submucosa scaffold containing 25,50,and 100 mg/mL nanohydroxyapatite(referred to as nHA-SIS scaffold)were prepared by 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride/N-hydroxysuccinimide cross-linking method.The appropriate scaffold was screened for subsequent experiments by mechanical property testing.The antibacterial properties of KR-12-a5 polypeptide solution against Staphylococcus aureus,Streptococcus gordonii,and Fusobacterium nucleatum were detected.The nHA-SIS scaffolds were immersed in 250,500,and 1 000 μg/mL KR-12-a5 peptide solutions for 24 hours,and then freeze-dried to obtain peptide-loaded nanohydroxyapatite-porcine small intestinal submucosa composite scaffolds(denoted as P-nHA-SIS scaffolds).The sustained-release properties of the three groups of scaffolds were characterized.The nHA-SIS scaffolds and the three groups of P-nHA-SIS scaffolds were co-cultured with Staphylococcus aureus,Streptococcus gordonii,and Fusobacterium nucleatum for 24 hours or 48 hours.The scaffolds with strong antibacterial ability were screened by live and dead bacteria staining and scanning electron microscopy for subsequent experiments.The degradation properties and water absorption rates of the uncross-linked small intestinal submucosa scaffolds,cross-linked small intestinal submucosa scaffolds,nHA-SIS scaffolds,and P-nHA-SIS scaffolds were characterized.The extracts of cross-linked small intestinal submucosal scaffolds,nHA-SIS scaffolds,and P-nHA-SIS scaffolds were co-cultured with MC3T3-E1 cells.CCK-8 assay and live-dead cell staining were performed.The effects of the extracts of the three scaffolds on the migration of MC3T3-E1 cells were detected by Transwell chamber assay.RESULTS AND CONCLUSION:(1)The elastic modulus and compressive strength of 25,50,and 100 mg/mL nHA-SIS scaffolds were higher than those of small intestinal submucosal scaffolds(P＜0.05),among which the elastic modulus and compressive strength of 25 mg/mL nHA-SIS scaffolds were the highest,and this group of scaffolds were selected for subsequent experiments to load peptides.(2)KR-12-a5 peptide had strong antibacterial activity against common bacteria in bone defects(Staphylococcus aureus,Streptococcus gordonii,and Fusobacterium nucleatum).The three groups of P-nHA-SIS scaffolds all had sustained release properties.With the increase of peptide mass concentration,the antibacterial property of P-nHA-SIS scaffold was enhanced.Among them,the P-nHA-SIS scaffold loaded with 500 μg/mL peptide had achieved a satisfactory antibacterial effect,and this group of scaffolds would be selected in the future.(3)The degradation rate of the three groups of cross-linked scaffolds was lower than that of the uncross-linked scaffolds,and the water absorption rate was greater than that of the uncross-linked scaffolds.P-nHA-SIS scaffolds could promote the proliferation and migration of MC3T3-E1 cells without affecting the activity of MC3T3-E1 cells.(4)The results show that P-nHA-SIS scaffolds have strong antibacterial properties and the ability to promote the proliferation and migration of MC3T3-E1 cells,and are expected to be used in bone defect repair.

Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

Traditional Chinese medicine (TCM) represents a paradigmatic approach to personalized medicine, developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years, and now encompasses large-scale electronic medical records (EMR) and experimental molecular data. Artificial intelligence (AI) has demonstrated its utility in medicine through the development of various expert systems (e.g., MYCIN) since the 1970s. With the emergence of deep learning and large language models (LLMs), AI's potential in medicine shows considerable promise. Consequently, the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction. This survey provides an insightful overview of TCM AI research, summarizing related research tasks from three perspectives: systems-level biological mechanism elucidation, real-world clinical evidence inference, and personalized clinical decision support. The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice. To critically assess the current state of the field, this work identifies major challenges and opportunities that constrain the development of robust research capabilities-particularly in the mechanistic understanding of TCM syndromes and herbal formulations, novel drug discovery, and the delivery of high-quality, patient-centered clinical care. The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality, large-scale data repositories; the construction of comprehensive and domain-specific knowledge graphs (KGs); deeper insights into the biological mechanisms underpinning clinical efficacy; rigorous causal inference frameworks; and intelligent, personalized decision support systems.
Medicine, Chinese Traditional/methods* ; Artificial Intelligence ; Humans ; Precision Medicine ; Decision Support Systems, Clinical

The prevalence of Class III malocclusion varies among different countries and regions. The populations from Southeast Asian countries (Chinese and Malaysian) showed the highest prevalence rate of 15.8%, which can seriously affect oral function, facial appearance, and mental health. As anterior crossbite tends to worsen with growth, early orthodontic treatment can harness growth potential to normalize maxillofacial development or reduce skeletal malformation severity, thereby reducing the difficulty and shortening the treatment cycle of later-stage treatment. This is beneficial for the physical and mental growth of children. Therefore, early orthodontic treatment for Class III malocclusion is particularly important. Determining the optimal timing for early orthodontic treatment requires a comprehensive assessment of clinical manifestations, dental age, and skeletal age, and can lead to better results with less effort. Currently, standardized treatment guidelines for early orthodontic treatment of Class III malocclusion are lacking. This review provides a comprehensive summary of the etiology, clinical manifestations, classification, and early orthodontic techniques for Class III malocclusion, along with systematic discussions on selecting early treatment plans. The purpose of this expert consensus is to standardize clinical practices and improve the treatment outcomes of Class III malocclusion through early orthodontic treatment.
Humans ; Malocclusion, Angle Class III/classification* ; Orthodontics, Corrective/methods* ; Consensus ; Child

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

OpenSim is an open source, free motion simulation and gait analysis software, which can be used to dynamically simulate and analyze the complex motion of the human body, and is widely used in human biomechanical research. Since OpenSim can analyze multi-dimensional motion data such as muscle strength, joint torque, and muscle synergistic activation during human movement, it can be used to study the biomechanical mechanism of musculoskeletal imbalance diseases and various treatment methods in TCM orthopedics, and has a broad application prospect in the field of TCM orthopedics. By the analysis of the basic characteristics, elements, analysis process, and application prospects of OpenSim, it is concluded that OpenSim musculoskeletal model has a large application space in the field of traditional Chinese medicine orthopedic, which is helpful to explain the pathogenesis and mechanism of diseases, and promote the precision diagnosis and treatment of orthopedics diseases;the application of OpenSim musculoskeletal model can solve the problem that the previous research paid attention to the bone malalignment and not enough attention to the tendon, and provide a new method for the research of orthopedic diseases. At present, there are still problems in the promotion and application of OpenSim, such as large equipment requirements and high operation threshold. Therefore, multidisciplinary cooperation, clinical research, and data sharing are the basic research strategies in this field.
Humans ; Biomechanical Phenomena ; Orthopedics ; Traumatology ; Software ; Medicine, Chinese Traditional ; Musculoskeletal System ; Models, Biological

The connection between tendons and bones is called the tendon bone connection. With the continuous improvement of national sports awareness, excessive exercises and the related intensity are prone to damage the tendon bone connection. Tendon bone healing is a complex repair and healing process involving multiple factors, and good tendon bone healing is a prerequisite for its physiological function. The complexity of tendon bone structure also poses great challenges to the repair of tendon bone injuries. In recent years, researches have found that stem cells, growth factors, macrophages, and other factors are closely related to the healing process of tendon bone injuries, among which macrophages play an important role in the healing process. The authors reviewed relevant research literature in recent years and summarized the role of macrophages in tendon bone healing, in order to provide new ideas and directions for treatment strategies to promote tendon bone healing.
Humans ; Macrophages/metabolism* ; Wound Healing ; Animals ; Tendons/physiology* ; Bone and Bones/injuries* ; Tendon Injuries

Objective Based on 25 indicators including immune factors, cell count classification, and smear results of the knee joint fluid, machine learning models were established to distinguish between osteoarthritis (OA) and rheumatoid arthritis (RA). Methods 100 OA and 40 RA patients scheduled for total knee arthroplasty were enrolled respectively. Each patient's knee joint fluid was collected preoperatively. Nucleated cells were counted and classified. The expression levels of immune factors, including tumor necrosis factor alpha (TNF-α), interleukin-1 beta (IL-1β), IL-6, IL-8, IL-15, matrix metalloproteinase 3 (MMP3), MMP9, MMP13, rheumatoid factor (RF), serum amyloid A (SAA), C-reactive protein (CRP), and others were measured. Smears and microscopic classification of all the immune factors were performed. Independent influencing factors for OA or RA were identified using univariate binary logistic regression, Lasso regression, and multivariate binary logistic regression. Based on the independent influencing factors, three machine learning models were constructed which are logistic regression, random forest, and support vector machine. Receiver operating characteristic curve (ROC), calibration curve and decision curve analysis (DCA) were used to evaluate and compare the models. Results A total of 5 indicators in the knee joint fluid were screened out to distinguish OA and RA, which were IL-1β(odds ratio(OR)=10.512, 95× confidence interval (95×CI) was 1.048-105.42, P=0.045), IL-6 (OR=1.007, 95×CI was 1.001-1.014, P=0.022), MMP9 (OR=3.202, 95×CI was 1.235-8.305, P=0.017), MMP13 (OR=1.002, 95× CI was 1-1.004, P=0.049), and RF (OR=1.091, 95×CI was 1.01-1.179, P=0.026). According to the results of ROC, calibration curve and DCA, the accuracy (0.979), sensitivity (0.98) and area under the curve (AUC, 0.996, 95×CI was 0.991-1) of the random forest model were the highest. It has good validity and feasibility, and its distinguishing ability is better than the other two models. Conclusion The machine learning model based on immune factors in the knee joint fluid holds significant value in distinguishing OA and RA. It provides an important reference for the clinical early differential diagnosis, prevention and treatment of OA and RA.
Humans ; Arthritis, Rheumatoid/metabolism* ; Machine Learning ; Male ; Female ; Middle Aged ; Aged ; Synovial Fluid/immunology* ; Osteoarthritis, Knee/metabolism* ; Knee Joint/metabolism* ; ROC Curve ; Diagnosis, Differential

PURPOSE: To analyze risk factors for severe trauma and establish a nomogram for early risk prediction, to improve the early identification of severe trauma. METHODS: This study was conducted on the patients treated in 81 trauma treatment institutions in Gansu province from 2020 to 2022. Patients were grouped by year, with 5364 patients from 2020 to 2021 as the training set and 1094 newly admitted patients in 2020 as the external validation set. Based on the injury severity score (ISS), patients in the training set were classified into 2 subgroups of the severe trauma group (n = 478, ISS scores ≥25) and the non-severe trauma group (n = 4886, ISS scores <25). Univariate and binary logistic regression analyses were employed to identify independent risk factors for severe trauma. Subsequently, a predictive model was developed using the R software environment. Furthermore, the model was subjected to internal and external validation via the Hosmer-Lemeshow test and receiver operating characteristic curve analysis. RESULTS: In total, 6458 trauma patients were included in this study. Initially, this study identified several independent risk factors for severe trauma, including multiple traumatic injuries (polytrauma), external hemorrhage, elevated shock index, elevated respiratory rate, decreased peripheral oxygen saturation, and decreased Glasgow coma scale score (all p < 0.05). For internal validation, the area under the receiver operating characteristic curve was 0.914, with the sensitivity and specificity of 88.4% and 87.6%, respectively; while for external validation, the area under the receiver operating characteristic curve was 0.936, with the sensitivity and specificity of 84.6% and 93.7%, respectively. In addition, a good model fitting was observed through the Hosmer-Lemeshow test and calibration curve analysis (p > 0.05). CONCLUSION This study establishes a nomogram for early risk prediction of severe trauma, which is suitable for primary healthcare institutions in underdeveloped western China. It facilitates early triage and quantitative assessment of trauma severity by clinicians prior to clinical interventions.
Humans ; Nomograms ; Male ; Female ; Wounds and Injuries/diagnosis* ; Risk Factors ; Middle Aged ; Adult ; Injury Severity Score ; Risk Assessment ; ROC Curve ; Aged ; Logistic Models ; China ; Glasgow Coma Scale