BACKGROUND:The local immune microenvironment plays an important regulatory role in the process of bone formation,and the immune system is intricately linked to the skeletal system.OBJECTIVE:To systematically review the promotion of bone regeneration from three aspects:immune cell regulation of microenvironment,regulation of immune response by small extracellular vesicles,and induction of immune response by bone biomaterials,and to elucidate the immune regulatory mechanisms involved in bone regeneration.METHODS:Relevant literature was retrieved from PubMed,CNKI,WanFang Database,and VIP Database,using the search terms of"osteoimmunology,immune microenvironment,small extracellular vesicles,bone regeneration,bone tissue repair,biomaterials,and tissue engineering"in English and Chinese.Repeat and irrelevant literature was screened and removed,and 92 articles that met the criteria were selected for intensive reading and review.RESULTS AND CONCLUSION:Multiple immune cells and bone cells are in the same microenvironment,and immune cells can regulate the differentiation and activity of bone cells,collectively forming an immune microenvironment that affects bone regeneration.Neutrophils can significantly reduce local inflammatory responses in the early stages of bone injury,creating a favorable microenvironment for bone regeneration.M1 macrophages can clear foreign bodies and reduce early inflammatory responses,while M2 macrophages can promote the expression of osteogenic markers and factors,playing an important role in the repair process of bone injury.B cells and T cells can directly or indirectly affect the generation and activity of osteoblasts and osteoclasts,regulate bone metabolism,and promote bone regeneration.Extracellular vesicles of small cells regulate the local immune microenvironment through paracrine secretion,promoting bone formation and angiogenesis at the site of bone injury.The metal ions,surface hydrophilicity,porosity,pore size,surface morphology,and surface roughness on the surface of biomaterials can directly regulate local immune responses,and have anti-inflammatory,angiogenic,and osteogenic effects,thereby accelerating bone regeneration.

BACKGROUND:In China,the patient population with osteonecrosis is large,and there is an urgent need to find new preventive targets to develop more effective treatment strategies.Metabolomics studies have shown that there is an association between human metabolites and osteonecrosis,but the causal relationship between blood metabolites and osteonecrosis has not yet been clarified.OBJECTIVE:To investigate the causal relationship between blood metabolites and osteonecrosis through two-sample Mendelian randomization analysis.METHODS:The public data of 486 blood metabolites(exposure factors)and osteonecrosis(outcome factors)were collected.Data of 486 blood metabolites were derived from a genome-wide association estimate for blood metabolites published in Nature Genetics in 2014,which covered 7 824 European adults.The single nucleotide polymorphism data for osteonecrosis were obtained from the FinnGen public database R11 dataset,containing information on a total of 431 614 samples and 21 306 430 single nucleotide polymorphism loci,with 1 788 cases of osteonecrosis and 429 826 controls,with all participants being of European descent.Mendelian randomization analysis(inverse variance weighting method,MR-Egger method,and weighted median method)was performed by Rstudio software,and then the heterogeneity test,horizontal pleiotropy test and Steiger directionality test were performed to ensure the robustness and reliability of the results.RESULTS AND CONCLUSION:(1)Sixteen blood metabolites were identified as having a significant causal relationship with osteonecrosis(Pinverse variance weighting＜Pfalse discovery rate＜0.05).(2)Eight blood metabolites increased the risk of osteonecrosis(including four known metabolites and four unknown metabolites),specifically pantothenate,beta-hydroxyisovalerate,hippurate,salicyluric glucuronide,X-08766,X-11452,X-12776 and X-14662.(3)Eight blood metabolites could reduce the risk of osteonecrosis(six known metabolites and two unknown metabolites),including cortisol,1-palmitoylglycerol(1-monopalmitin),pyroglutamyl glycine,2-stearoylglycerophosphocholine,p-cresol sulfate,ergothioneine,X-06307,X-12092.(4)The above results suggest that there is a causal relationship between 16 blood metabolites and osteonecrosis,which is expected to be a potential target for intervention in the occurrence and treatment of osteonecrosis in the future.(5)Despite the lack of relevant data from large-scale Asian populations at present,this study provides important reference value for the field of osteonecrosis in China based on European population data.In the future,domestic medical workers may be able to achieve precise intervention for osteonecrosis by regulating metabolite levels.In addition,based on the results of this study,relevant researchers can further explore the mechanism of action of metabolites in the treatment of osteonecrosis with traditional Chinese medicine,which not only helps to deepen the understanding of traditional Chinese medical therapies but also promotes the progress of integrated traditional Chinese and Western medicine research,driving the development of personalized treatment plans that are more suitable for the characteristics of the Chinese population.

Radiotherapy is a crucial treatment modality for head and neck tumors. However, while effectively killing tumor cells, it significantly disrupts the homeostasis of the oral microecology, which is closely associated with various complications such as radiation-induced oral mucositis. Literature review indicates that as radiotherapy doses accumulate and treatment durations extend, the richness and diversity of the oral microbiota show a declining trend, with the genus Streptococcus decreasing most markedly. In contrast, radiotherapy selectively promotes the proliferation of bacterial phyla such as Proteobacteria and Bacteroidetes, which are rich in opportunistic pathogens. Mechanistically, radiotherapy activates the nuclear factor-kappa B pathway, triggering chronic inflammation and oxidative stress, damaging the epithelial barrier, suppressing local immunity, and causing damage to organs such as the salivary glands. It can also induce systemic diseases via the oral-gut axis, forming a multi-level, interconnected pathogenic network. In terms of interventions, treatment strategies including probiotics and prebiotics have shown promising efficacy against side effects such as radiation-induced oral mucositis. Saliva-based oral microbiota transplantation is an emerging strategy that is expected to become widely utilized for restoring oral microecological balance. Existing interventions provide preliminary pathways for clinical practice, but this field still faces several key scientific questions. The association between oral microecology and systemic diseases remains largely correlative, lacking causal evidence. Furthermore, critical parameters for oral microbiota transplantation, such as donor screening criteria, transplantation protocols, and long-term safety, are not yet well-defined. Therefore, future research should focus on conducting large-scale clinical trials to establish standardized protocols and safety evaluation systems for oral microecological interventions, and explore combined treatment therapies such as probiotics, prebiotics, and microbiota transplantation to advance the development of personalized precision modulation. These will enable more effective management of radiotherapy-induced oral microecological dysbiosis and improve treatment outcomes and quality of life for patients with head and neck tumors.

Objective: To explore the value of contrast-enhanced computed tomography (CT) radiomics combined with machine learning algorithms in the preoperative prediction of perineural invasion (PNI) in oral squamous cell carcinoma (OSCC), aiming to provide evidence for assisting clinical treatment decision-making. Methods​: This study was approved by the Ethics Committee of the Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine. A total of 250 OSCC patients confirmed by postoperative pathology were included, comprising 128 PNI-positive and 122 PNI-negative cases. The dataset was randomly divided into training (n=175), validation (n=38), and independent testing (n=37) sets in a ratio of 7:1.5:1.5. Regions of interest were delineated on preoperative images, and radiomic features were extracted. After dimensionality reduction and feature selection using methods like Least Absolute Shrinkage and Selection Operator (LASSO) regression, multiple machine learning models, including support vector machine (SVM), random forest, Light gradient boosting machine (LightGBM), and a Stacking ensemble model, were constructed. Model performance was evaluated using metrics such as the area under the receiver operating characteristic curve (AUC), sensitivity, calibration curves, and decision curve analysis (DCA). Model interpretability was analyzed using Shapley additive explanations (SHAP) and grouped permutation feature importance analysis. Results ​: ​ Among the 250 samples analyzed, the LightGBM model based on radiomics demonstrated the best performance on the independent test set, with an AUC of 0.781, outperforming models like SVM (AUC = 0.730) and Random Forest (AUC = 0.691), as well as clinical models (AUCs ranging 0.549-0.711). The LightGBM model showed good calibration (Brier score 0.198), and DCA indicated high clinical net benefit over a wide threshold probability range. Paired DeLong tests revealed no statistically significant differences in AUC between the ensemble (Stacking) model and the corresponding best-performing radiomics-based model. SHAP analysis and grouped permutation feature importance analysis further indicated that the primary discriminative information for the model came from radiomic texture features. Conclusion ​ The LightGBM model based on contrast-enhanced CT radiomics demonstrated good discriminative ability for preoperative prediction of PNI in OSCC. In the independent test set, it achieved the highest AUC. This model holds promise as a non-invasive auxiliary tool for preoperative risk assessment. Given the limited sample size of the independent test set, these results require further validation in larger cohorts and external datasets.

Elderly patients with lung cancer have a significantly increased risk of perioperative cardiopulmonary complications due to physiological decline, high incidence of complications and reduced surgical tolerance, which directly affects postoperative recovery and long-term survival. Although the concepts of minimally invasive surgery and enhanced recovery after surgery have improved clinical outcomes, early recognition and intervention of postoperative complications in elderly patients remains a significant challenge in the field of thoracic surgery. By integrating recent literature and clinical practice, this paper systematically analyzes the pathophysiological mechanism and risk factors of perioperative cardiopulmonary complications in elderly patients with lung cancer, and discusses individualized intervention strategies based on risk stratification and multidisciplinary team, in order to provide theoretical basis and practical guidance for optimizing perioperative management and improving postoperative prognosis in elderly patients.

Cuproptosis, recently defined as a unique form of cell death distinct from programmed cell death, is triggered by copper overload within mitochondria. Genes associated with cuproptosis have been found to correlate with tumorigenesis and tumor progression, making the targeting of cuproptosis pathways a promising direction for anti-tumor therapies. Copper ion carriers can transport copper ions into cells, inducing cuproptosis and laying the foundation for its application in cancer treatment. This article elaborates on the homeostasis of copper and the mechanisms related to cuproptosis, further clarifying the relationship between cuproptosis and lung cancer treatment targets. This review aims to summarize current progress in research related to cuproptosis and lung cancer, providing new theories and bases for the clinical treatment of lung cancer.

In recent years， repetitive transcranial magnetic stimulation （rTMS） has garnered significant attention as a therapeutic approach for sleep disorders in the elderly. However， the prevailing rTMS protocols are predominantly developed based on normative neurophysiological data derived from young adults and fail to incorporate individualized parameters tailored to the brain characteristics of the elderly. To address this gap， the consensus development group synthesized the latest evidence from 2010 to 2025 and established a standardized rTMS protocol specifically for elderly patients with sleep disorders. Adhering to the Appraisal of Guidelines for Research and Evaluation II （AGREE II） framework， systematically screened randomized controlled trials （RCTs） and systematic reviews regarding rTMS in the treatment of sleep disorders across various conditions. Meanwhile， the Grading of Recommendations Assessment， Development and Evaluation （GRADE） system was employed to rigorously grade the quality of evidence and the strength of recommendations. This consensus guideline delineates precise rTMS protocols for the management of sleep disorders in the elderly， highlights the adjustment of stimulation intensity according to scalp-cortex distance recommends either MRI‑guided neuronavigation or the Beam F3/F4 heuristic approach for accurate target localization， thereby providing precise rTMS intervention protocol for sleep disorders in the elderly， aiming to enhance clinical efficacy while ensuring treatment safety. ［Funded by National Key Research and Development Program （number， 2023YFC3603200）； General Program of Shenzhen Science and Technology Innovation Commission （number， JCYJ20240813112859008， JCYJ20240813112900002）； Youth Program of Shenzhen Kangning Hospital （number， KN2023A004）； www.guidelines-registry.cn number， PREPARE-2026CN530］

Objective To investigate occupational exposure levels of lead, arsenic and cadmium in the lead smelting plant of Hunan Shui Kou Shan Nonferrous Metals Group Co. Ltd., analyze their effects on health of employees, and compare the applicability of different occupational health risk assessment methods, and to provide a basis for prevention and control of occupational exposure risks in enterprises. Methods According to systematic sampling method, 380 employees with lead, arsenic and cadmium exposure (exposure group) and 100 non-exposure employees (non-exposure group) were selected from 2022 to 2024 for on-site investigation of occupational health [concentration time-weighted average (C_TWA)] and physical examination. The risk was evaluated by qualitative assessment method, the U.S. Environmental Protection Agency (EPA) inhalation risk assessment method, and the Singapore Ministry of Manpower (MOM) semi-quantitative method. The consistency was analyzed by the Kappa test. Results C_TWA values of lead, arsenic, and cadmium in all positions were lower than the occupational exposure limit (OEL). The levels of blood lead, urine arsenic, and urine cadmium, as well as the prevalence of multiple systems in the exposure group were significantly higher than those in the non-exposure group (P<0.05). The proportions of chronic lead, arsenic, and cadmium poisoning were increasing year by year in the exposure group (P<0.05). The qualitative assessment method mainly indicated low and medium risk, while the EPA and MOM methods mainly indicated medium and high risk, with good agreement between the two methods (Kappa=0.676, P<0.05). Conclusion Although the enterprise meets the C_TWA standards, there are still occupational health risks of lead, arsenic, and cadmium. The EPA inhalation risk assessment method is more applicable.

Objective To explore the correlation between anxiety and depression, treatment compliance and social support level in elderly patients with coronary heart disease. Methods A cross-sectional study was conducted on 325 patients with coronary heart disease who were treated in this hospital from June 2023 to June 2025 Pearson correlation analysis was used to examine the correlations between the level of social support [Social Support Rating Scale (SSRS)] and treatment compliance [12-item Medication Compliance Scale (MAS)], anxiety [Hamilton Anxiety Scale (HAMA)], and depression [Hamilton Depression Scale (HAMD)]. Logistic regression analysis was conducted to analyze the factors related to treatment compliance of coronary heart disease. Results SSRS score was positively associated with MAS score, and negatively correlated with HAMA score and HAMD score in patients with coronary heart disease (P<0.05). Logistic regression analysis suggested that age, education level, living alone, cardiac function grading, mini-mental state examination scale score, SSRS score, HAMA score and HAMD score were independently correlated with treatment compliance in patients with coronary heart disease (P<0.05). Conclusion The level of social support in patients with coronary heart disease is positively correlated with treatment compliance, and negatively correlated with anxiety and depression, and social support level, anxiety and depression are independent related factors affecting treatment compliance.

Objective To explore the prevalence of depressive symptoms in postoperative patients with ovarian cancer and to analyze its influencing factors from multiple dimensions, including clinical characteristics, psychological factors, and laboratory indicators. Methods A cross-sectional study was conducted, which enrolled 235 postoperative patients with ovarian cancer. Depressive status was assessed using the patient health questionnaire, and the demographic, pathological, and medical record data of the patients were collected using the generalized anxiety disorder scale, Pittsburgh sleep quality index, European organization for research and treatment of cancer quality of life questionnaire core 30, and ECOG performance status score. Peripheral blood tumor marker (CA125), routine blood test, lymphocyte subsets, and serum cytokine levels were measured. Univariate and multivariate binary logistic regression analysis were used for statistical analysis. Results The prevalence of depression in postoperative patients with ovarian cancer was 39.15% (92/235). Univariate analysis showed that ECOG score ≥ 2 points, pain, anxiety, poor sleep quality, low quality of life, low life satisfaction, tumor recurrence, six or more cycles of chemotherapy, as well as higher levels of CA125, NLR, and NAR, and lower hemoglobin levels were significantly associated with depression (all P<0.05). Multivariate binary Logistic regression analysis showed that anxiety (OR=1.975, 95%CI: 1.231-3.170), sleep efficiency (OR=4.181, 95%CI: 1.211-14.43), sleep latency (OR=34.806, 95%CI: 4.258-284.542), ECOG performance status score, cognitive function (OR=0.918, 95%CI: 0.868-0.97), and life satisfaction were independent risk factors for depression (all P<0.05). Laboratory indicators were not independent influencing factors in the multivariate Logistic regression model. Conclusion Depression in postoperative patients with ovarian cancer is influenced by physiological, psychological, and social factors. Clinical management should focus on patients with anxiety, sleep disorders, poor physical condition, and low life satisfaction, and a comprehensive prevention and treatment strategy centered on psychological intervention and taking into account symptom management and social support should be implemented.