Osteoporosis （OP） is a metabolic disorder characterized by microstructural deterioration of bone and increased bone fragility due to reduced bone mass， which can cause the development of bone-related diseases. This condition imposes significant economic and psychological burdens on patients. While modern medicine has extensively researched the pathogenesis of OP， it remains incompletely understood. Current clinical management primarily relies on anti-resorptive drugs and synthetic metabolic agents. However， long-term use of some medications may yield suboptimal therapeutic outcomes and lead to severe adverse reactions. Given the necessity for prolonged or lifelong treatment for OP， there is a critical need to identify highly effective， safe， and cost-effective pharmaceutical interventions. In light of evolving disease management paradigms and recent advancements in OP research， traditional Chinese medicine has demonstrated emerging advantages in addressing this condition. Through literature review， this study delves into the pathogenesis of OP from five perspectives： hormonal dysregulation， autophagy， ferroptosis， oxidative stress， and intestinal flora alteration. Furthermore， it summarizes the therapeutic efficacy and specific mechanisms of traditional Chinese medicine monomers and compound formulas against OP through regulating hormone levels， interfering with autophagy， inhibiting ferroptosis， counteract oxidative stress，and maintain intestinal flora balance. These multifaceted insights are expected to provide theoretical reference and guide future clinical traditional Chinese medicine approaches for preventing and managing OP.

The aim of this paper is to present the basic principles of the mesh basket-like six-electrode renal denervation (RDN) system, research progress in anti-hypertensive therapy and modulation of autonomic nerves for the treatment of diseases. It discusses the advances in system design, operational optimization and expansion of clinical applications, as well as the challenges faced. The future prospects of personalized autonomic nerves modulation for the treatment of diseases are also discussed.

BACKGROUND:The pathogenesis of rheumatoid arthritis has not yet been fully clarified,and recent studies have shown that mitophagy is associated with rheumatoid arthritis,but the key mechanisms need to be explored in depth.OBJECTIVE:To identify and validate the core interaction genes of mitophagy in rheumatoid arthritis using multiple machine learning algorithms and to analyze its immunoregulatory process.METHODS:The rheumatoid arthritis transcriptome expression dataset GSE15573 was retrieved from the GEO database as an independent training set,with the GSE97779 and GSE55235 collections used as independent validation sets.The differentially expressed genes of rheumatoid arthritis were screened using the training set,and"WGCNA"analysis was also performed.Then we downloaded the mitophagy-related genes from the"MitoCarta3.0"database,and intersected them with the differentially expressed genes of rheumatoid arthritis and the genes in the"WGCNA"analysis module to obtain the rheumatoid arthritis-mitophagy-related genes,and then analyzed the related genes for functional enrichment to clarify the cellular pathways.Feature genes were initially identified using the"Random Forest"and"Lasso"algorithms.The overlapping genes from these two methods were further refined using the"GMM"algorithm to identify the core interaction genes between rheumatoid arthritis and mitophagy.A predictive model was then developed and validated using an external dataset.Finally,"CIBERSORT"was employed to analyze the proportions and interactions of immune cell subsets during immune infiltration,while"ssGSEA"was used to examine the associations between the rheumatoid arthritis-mitophagy core interaction genes and immune cell subsets."ssGSEA"was also utilized to analyze the"GO"and"KEGG"biological pathways of the core interaction genes.RESULTS AND CONCLUSION:(1)Totally 807 differentially expressed genes in rheumatoid arthritis were obtained by differential analysis,1 208 genes were selected from two feature modules by"WGCNA"analysis,1136 genes were sorted out from the MitoCarta 3.0 database,and 53 HUB genes were obtained from the intersection of the three genes as rheumatoid arthritis-mitophagy related genes.(2)The results of functional enrichment analysis of related genes showed that the cellular processes were mainly related to mitophagy,peroxisome metabolism,cellular senescence,and necroptosis.(3)The three machine learning algorithms identified four rheumatoid arthritis-mitophagy core interaction genes(DNAJA3,C12orf65,AKR7A2,and PDHB).The area under the curve of nomoscore was 0.989,and the area under the curve values of rheumatoid arthritis-mitophagy core interaction genes verified by the receiver operating characteristic curve of external patient samples were all greater than 0.7.(5)Immunoregulatory analysis showed that the mitophagy process in rheumatoid arthritis was closely associated with memory B cells,M0 macrophages,activated memory CD4 T cells,and resting memory CD4 T cells.(6)The biological pathway analysis revealed that the core interaction genes were strongly associated with 821"GO"pathways(|cor|＞0.8,P＜0.001)and 48"KEGG"pathways(|cor|＞0.8,P＜0.001).The key biological processes identified were related to mitochondrial DNA metabolic process,mitochondrial DNA repair,mitochondrial DNA replication,mitochondrial genome maintenance,positive regulation of mitochondrial depolarization,and positive regulation of mitochondrial outer membrane permeabilization involved in apoptotic signaling pathway.To conclude,DNAJA3,C12orf65,AKR7A2,and PDHB are the core interaction genes of the mitophagy process in rheumatoid arthritis,which play key roles in disease progression by participating in specific immune processes and have precise and predictive effects on the diagnosis of rheumatoid arthritis.

Ovulatory dysfunction (OD) is one of the main causes of infertility in women of childbearing age, which not only affects their reproductive ability, but also physical and mental health. Traditional treatment strategies have limited efficacies, and the emergence of biomedicines provides a promising alternative solution via the strategies of combining engineered design with modern advanced technology. This review explores the pathophysiological characteristics and related induction mechanisms of OD, and evaluates the current cutting-edge advances in its treatments. It emphasizes the potentials of biomedicines strategies such as hydrogels, nanoparticles and extracellular vesicles in improving therapeutic precision and efficacy. By mimicking natural physiological processes, and achieving controlled drug release, these advanced drug carriers are expected to address the challenges in ovarian microenvironment reprogramming, tissue repair, and metabolic and immune regulation. Despite the promising progress, there are still challenges in terms of biomedical complexity, differences between animal models and human physiology, and the demand for intelligent drug carriers in the therapy of OD. Future researches are mainly dedicated to developing precise personalized biomedicines in OD therapy through interdisciplinary collaboration, promoting the development of reproductive regenerative medicine.

BACKGROUND:Mitochondrial autophagy is closely related to the occurrence and development of steroid-induced osteonecrosis of the femoral head(SONFH),but specific biomarkers and regulatory mechanisms remain unclear. OBJECTIVE:To identify the key biomarkers of mitochondrial autophagy in steroid-induced osteonecrosis of the femoral head using machine learning algorithms and to conduct an immune infiltration analysis. METHODS:The SONFH datasets GSE123568 and GSE74089 were downloaded from the GEO database,serving as the training and validation sets,respectively.Differentially expressed genes between SONFH and control groups were selected,and weighted gene co-expression network analysis was performed.Mitochondrial autophagy-related genes were obtained from MitoCarta3.0 and intersected with differentially expressed genes and module genes.Two machine learning algorithms were utilized to identify key genes of SONFH mitochondrial autophagy,and validated using an external validation set.CIBERSORT and immune infiltration analysis were employed to assess the proportion of immune cells,and ssGSEA was used to analyze the correlation between mitochondrial autophagy genes and immune cells. RESULTS AND CONCLUSION:Differential analysis identified a total of 1 163 differentially expressed genes,including 663 upregulated genes and 500 downregulated genes.Weighted gene co-expression network analysis identified 4 key modules,comprising 1 412 module genes.Intersection with mitochondrial autophagy genes yielded 39 intersecting genes as disease-related mitochondrial autophagy genes.Gene ontology enrichment analysis showed that the biological processes were mainly related to heme metabolism,mitochondrial transport,nucleotide bisphosphate metabolism and thioester metabolism,and the cellular components were mainly related to mitochondrial matrix,mitochondrial outer membrane,organelle outer membrane and mitochondrial inner membrane,and the molecular functions were mainly related to fatty acid ligase activity,iron-sulfur cluster binding,and cofactor A ligase activity.Kyoto Encyclopedia of Genes and Genomes enrichment analysis mapped out a total of six pathways,which were mainly related to fatty acid degradation,mitochondrial autophagy,butyric acid metabolism,fatty acid biosynthesis and cofactor biosynthesis.Through LASSO regression and RFE-SVM algorithm analysis,four intersecting genes(ALDH5A1,FBXL4,MCL1,and STOM)were identified.The receiver operating characteristic curves of the four core genes and the diagnostic column chart validation set were all greater than 0.9.The occurrence and development of SONFH were related to immune cells such as dendritic cells,bone marrow-derived suppressor cells,regulatory T cells,and central memory CD8 T cells.To conclude,the four key mitochondrial autophagy genes ALDH5A1,FBXL4,MCL1,and STOM play a crucial role in the progression of SONFH through osteoclast differentiation and immune mechanisms.Additionally,all four genes have good disease prediction efficacy and can serve as biomarkers for the diagnosis and treatment of SONFH.

Objective:To analyze differences in the expression of routine laboratory parameters and cerebrospinal fluid (CSF) examination indicators between patients with non-neurosyphilis (syphilis without nervous system involvement) and those with neurosyphilis, to screen for key predictive factors, and to construct a predictive model for neurosyphilis.Methods:A retrospective analysis was conducted on the clinical data from patients with syphilis at the Fifth People's Hospital of Suzhou from 2019 to 2024. Patients with neurosyphilis and non-neurosyphilis who were hospitalized from November 2019 to June 2022 were included in the model cohort, and those hospitalized from January 2024 to October 2024 were included in the validation cohort. The patients' basic information and laboratory test indicators (including routine blood tests, CSF biochemical analysis, and syphilitic antibody tests) were collected. Statistical analysis was performed using the GraphPad software. The receiver operating characteristic (ROC) curve and the binary logistic regression method were used to analyze the predictive performance of key indicators in patients from the model cohort with SPSS software, and a predictive model for neurosyphilis was constructed. The performance of the neurosyphilis predictive model for neurosyphilis was validated based on relevant indicators from the validation cohort.Results:The model cohort included 99 patients with non-neurosyphilis (including 49 males and 50 females), and they were aged between 19 and 85 years, with an average age of 47 years; 69 patients with neurosyphilis were also included in the model cohort, including 58 males and 11 females, and they were aged between 26 and 73 years, with an average age of 51 years. The neurosyphilis group showed a significant increase in the median levels of CSF adenosine deaminase (1 U/L) and microprotein (711 mg/L), white blood cell counts (0.009 × 10?/L), as well as in the proportion of positive Pandy tests (35/69, 50.7%) compared with the non-neurosyphilis group (0 U/L, 309 mg/L, 0.002 × 10?/L, 2 /99 [2.0%], respectively, all P < 0.001). Based on the ROC curve analysis, the CSF microprotein and white blood cell count had relatively high discriminative ability (area under the ROC curve [AUC] > 0.85), while adenosine deaminase and the Pandy test showed moderate discriminative ability (0.7 < AUC < 0.85). According to the above four indicators, the logistic regression analysis showed that CSF microprotein combined with CSF white blood cell counts could construct the best predictive model for neurosyphilis, with a prediction accuracy rate of 0.980, a sensitivity of 98.5%, and a specificity of 89.9%. The prediction formula was logit (p) = -9.926 + 0.015 × microprotein + 362.33 × CSF white blood cell count, with a cutoff value of ≥ -0.867. The validation cohort enrolled 72 patients with non-neurosyphilis and 51 with neurosyphilis, and there were significant differences in CSF microprotein levels and white blood cell counts between the two groups (both P < 0.001). In the validation cohort, the predictive model demonstrated an accuracy of 86.2%, with a sensitivity of 83.6% and a specificity of 91.1% for predicting neurosyphilis. Conclusion:The predictive model for neurosyphilis constructed by combining CSF microprotein and CSF white blood cell count may contribute to the early differential diagnosis of neurosyphilis.

Objective:To investigate the long-term efficacy, safety and prognostic factors of intraoperative radiotherapy (IORT) for narrow-margin (resection margin < 1 cm) hepatectomy in patients with hepatocellular carcinoma (HCC) during radical surgery.Methods:A retrospective cohort study was conducted. The data of primary HCC patients undergoing radical surgery and narrow-margin hepatectomy IORT in the Cancer Hospital of the Chinese Academy of Medical Sciences from November 2009 to February 2019 were collected. IORT applied 6 MeV or 9 MeV electron beams and a single irradiation was given to the margin. Kaplan-Meier method was used for the overall survival (OS) and disease-free survival (DFS) analysis; log-rank test was used for survival comparison among subgroups. The recurrence patterns and adverse reactions were recorded. Univariate and multivariate Cox proportional hazards models were used to analyze the factors influencing the OS and DFS.Results:A total of 64 patients were enrolled, with the median age [ M ( Q1, Q3)] of 57 years (49, 63) years. All patients included 55 males (85.9%) and 9 females (14.1%). The median dose of IORT was 15 Gy (range: 12-17 Gy). The median follow-up time was 83.3 (64.4, 91.9) months. The 1-year, 3-year, 5-year, 7-year, 10-year OS rates were 90.4%, 80.6%, 75.5%, 71.4% and 47.6%, respectively; the 1-year, 3-year, 5-year, 7-year,10-year DFS rates were 77.8%, 68.1%, 59.6%, 57.6% and 38.4%, respectively. Univariate Cox regression analysis indicated that preoperative serum alpha-fetoprotein (AFP) > 400 ng/ml was an independent risk factor for poor OS (> 400 ng/ml vs. ≤ 400 ng/ml: HR = 6.57, 95% CI: 2.16-19.96, P < 0.001), while not the independent influencing factor of poor DFS ( HR = 1.71, 95% CI: 0.65-4.52, P = 0.277). The age ≤ 60 years or not, gender, viral hepatitis or not, American Joint Committee on Cancer stage, tumor diameter (> 5 cm or not), tumor number, degree of tumor differentiation, microvascular invasion or not, microsatellite nodules or not, anatomical liver resection or not, and the dose of IORT ≤15 Gy or not were not the independent influencing factors of poor OS and DFS (all P > 0.05). Kaplan-Meier method analysis showed that patients with preoperative serum AFP ≤ 400 ng/ml (48 cases) had better OS compared with those with preoperative serum AFP>400 ng/ml (16 cases) (5-year OS rate: 84.8% vs. 44.9%; 7-year OS rate: 79.9% vs.37.4%), and the difference was statistically significant ( P = 0.002). There was no statistically significant difference in the DFS between the 2 groups ( P = 0.134). During the follow-up, 28 patients (43.8%) relapsed, including 17 cases (26.6%) of early recurrence and 11 cases (17.2%) of late recurrence. No marginal recurrence was observed. There were 22 cases (34.4%) of intrahepatic recurrence alone, 2 cases (3.1%) of extrahepatic recurrence and 4 cases (6.3%) of stimutaneous recurrence inside and outside the liver. The 1-, 3-, 5- and 7-year cumulative recurrence rates inside the liver were 19.0%, 27.2%, 37.4% and 39.3% respectively, and the cumulative recurrence rates outside the liver were 6.4%, 8.0%, 9.6% and 9.6% respectively. There were no adverse reactions above grade 3 in the entire group. There were no surgery-related deaths within 30 d after the operation, and no radiation-induced liver disease occurred. Conclusions:Narrow-margin IORT helps HCC patients receiving hepatectomy to achieve favorable long-term survival and adverse reactions are tolerable. It can be used as a safe and effective adjuvant therapy alternative.

Purpose This study aimed to evaluate the consistency of human epidermal growth factor receptor 2(HER2)status between primary breast cancer lesions and lung metastatic lesions and to establish a prognostic model for predicting the survival rate of HER2 low expression(HER2-low)breast cancer patients with lung metastasis.Methods Clinicopathological data from a cohort of 252 patients with breast cancer and lung metastasis were retrospec-tively analyzed.Results 50.00％of the patients had HER2-low expression in metastatic lesions,and HER2-low ex-pression was the most prevalent subgroup in both primary and metastatic lesions.A discordance in HER2 status be-tween primary and metastatic sites was observed in 28.07％of cases.The most frequent shift was from HER2-zero in the primary tumor to HER2-low expression in the metastasis(12.28％of all cases).Estrogen receptor(ER)status,menopausal status,and histological type were identified as independent prognostic factors for overall survival(OS)by univariate and multivariate Cox regression analyses.A prognostic model incorporating these factors was constructed to predict 3-year and 5-year survival.The model demonstrated area under the curve(AUC)values of 0.765 and 0.780 for 3-year and 5-year OS in the training cohort,and 0.667 and 0.706 in the validation cohort,respectively.Conclu-sion HER2-low expression is the most common subtype among breast cancer patients with lung metastasis.The ob-served shift from HER2-zero in primary lesions to HER2-low in metastases underscores the clinical necessity of re-biop-sy at metastatic sites.The developed prognostic model effectively predicts OS in this patient population.

Objective To explore the value of analysis on the incidence of healthcare-associated infection(HAI)based on disease diagnosis-related grouping(DRG),case mix index(CMI),and relative weight(RW).Methods All discharged cases,DRG and HAI status in a tertiary first-class general hospital from January 1 to December 31,2023 were analyzed retrospectively.Incidences of HAI in different departments were adjusted and compared by CMI.Incidences of HAI in different DRG groups were adjusted by RW.Results Among the 47 695 cases included in the analysis,757 were HAI cases,including 225 DRG groups.The department of critical care medicine had the highest incidence of HAI(11.98％).After CMI adjustment,departments with higher incidence of HAI were main-ly the department of respiratory and critical care medicine(3.96％),department of critical care medicine(3.04％),and department of neurology(2.85％),et al.DRG groups with the top five high incidence of HAI were AH11(tracheotomy and with ventilator support ≥96 hours or extracorporeal membrane oxygenation[ECMO],accompa-nied by major complications and comorbidity[MCC],50.00％),BC29(ventricular shunt and revision surgery,31.43％),BB21(craniotomy other than trauma,accompanied by MCC,27.56％),BB11(craniotomy of brain trauma,accompanied by MCC,26.32％),and GB1A(major surgery of esophagus,stomach,and duodenum,accompanied by major or moderate complications and comorbidity,16.00％).After RW adjustment,the DRG groups with the top five high incidence of HAI were ES21(respiratory system infection/inflammation,accompanied by MCC,5.89％),BR21(cerebral ischemic disease,accompanied by MCC,5.17％),FR11(heart failure,shock,accompanied by MCC,4.80％),BC29(4.57％)and AH11(3.57％).Conclusion Analyzing the incidence of HAI based on CMI and RW can help to identify key departments and disease groups for infection prevention and control,and provide reference for precise prevention and control of HAI in the new era.

Objective This study aims to investigate the effects of FGL2 on the immune response of EBV-infected T cells,including their activation,proliferation,exhaustion,and cytokine profile changes.Methods Primary T cells were infected with EBV at different multiplicities of infection(MOI).Expression of FGL2 in T cells,as well as T-cell activation,proliferation,exhaustion,and cytokine levels,were detected using RT-qPCR,Western blot,ELISA,CCK8,and flow cytometry(FCM),respectively.Further experiments involving FGL2 knockdown and overexpression were conducted to elucidate its specific regulatory role in EBV-infected T cells.Results FGL2 expression was significantly upregulated in EBV-infected T cells(P＜0.05).EBV infection also induced enhanced T cell activation(P＜0.001),proliferation(P＜0.001),and exhaustion(P＜0.01).Compared to the T cells+EBV group,the T cells+EBV+FGL2 overexpression group exhibited higher exhaustion levels(P＜0.01),reduced activation(P＜0.05)and proliferation(P＜0.05),decreased pro-inflammatory cytokine levels(P＜0.05),and increased anti-inflammatory cytokine levels(P＜0.05).Conversely,the T cells+EBV+FGL2 knockdown group demonstrated the opposite trends,with elevated activation(P＜0.01),proliferation(P＜0.05),pro-inflammatory cytokine levels(P＜0.05),and reduced exhaustion(P＜0.01)and anti-inflammatory cytokine levels(P＜0.05).Conclusion FGL2 suppresses T cell activation and proliferation,exacerbates T cell exhaustion,inhibits pro-inflammatory cytokine release,and promotes anti-inflammatory cytokine secretion during EBV infection,thereby modulating the immune response of T cells.