Chronic obstructive pulmonary disease（COPD） is a common chronic respiratory disorder frequently accompanied by diaphragmatic dysfunction during its course， which significantly increases respiratory burden and impairs quality of life. As the primary inspiratory muscle， the diaphragm is prone to fatigue， atrophy， inflammation， and fibrosis during the long-term progression of COPD. Its pathological mechanisms involve multiple pathways such as inflammatory responses， oxidative stress， mitochondrial dysfunction， apoptosis， ion channel abnormalities， epigenetic regulation， autophagy disorder， and protein metabolism imbalance. In recent years， traditional Chinese medicine（TCM） has demonstrated multi-targeted and systemic regulatory advantages in improving diaphragmatic function in COPD. However， related studies remain fragmented， and integrated mechanistic understanding is lacking. This paper focuses on the mechanism-target-TCM intervention framework， systematically summarizing the molecular mechanisms of diaphragmatic dysfunction， while incorporating the TCM theory of Zongqi（ancestral Qi）. It highlights the therapeutic effects of Chinese herbal formulas， single herbs， and active components in modulating inflammation， oxidative stress， mitochondrial function， ion channels， epigenetic processes， autophagy， and protein homeostasis. Additionally， the review outlines existing challenges， including insufficient study volume， unbalanced selection of herbal prescriptions， limited mechanistic depth， inconsistent disease models and experimental designs， lack of standardized diaphragmatic function assessment， and weak clinical validation. Future research should strengthen the integration of TCM and modern medicine， identify additional therapeutic targets， deepen mechanistic research， and establish unified and standardized experimental systems to advance the theoretical foundation and clinical application of TCM in the prevention and treatment of COPD-related diaphragmatic dysfunction.

Chronic obstructive pulmonary disease（COPD） is a common chronic respiratory disorder frequently accompanied by diaphragmatic dysfunction during its course， which significantly increases respiratory burden and impairs quality of life. As the primary inspiratory muscle， the diaphragm is prone to fatigue， atrophy， inflammation， and fibrosis during the long-term progression of COPD. Its pathological mechanisms involve multiple pathways such as inflammatory responses， oxidative stress， mitochondrial dysfunction， apoptosis， ion channel abnormalities， epigenetic regulation， autophagy disorder， and protein metabolism imbalance. In recent years， traditional Chinese medicine（TCM） has demonstrated multi-targeted and systemic regulatory advantages in improving diaphragmatic function in COPD. However， related studies remain fragmented， and integrated mechanistic understanding is lacking. This paper focuses on the mechanism-target-TCM intervention framework， systematically summarizing the molecular mechanisms of diaphragmatic dysfunction， while incorporating the TCM theory of Zongqi（ancestral Qi）. It highlights the therapeutic effects of Chinese herbal formulas， single herbs， and active components in modulating inflammation， oxidative stress， mitochondrial function， ion channels， epigenetic processes， autophagy， and protein homeostasis. Additionally， the review outlines existing challenges， including insufficient study volume， unbalanced selection of herbal prescriptions， limited mechanistic depth， inconsistent disease models and experimental designs， lack of standardized diaphragmatic function assessment， and weak clinical validation. Future research should strengthen the integration of TCM and modern medicine， identify additional therapeutic targets， deepen mechanistic research， and establish unified and standardized experimental systems to advance the theoretical foundation and clinical application of TCM in the prevention and treatment of COPD-related diaphragmatic dysfunction.

Objective To investigate the effects of combined exposure to benzene series, dust and noise on occupational high-frequency hearing loss (HFHL) in the electronics manufacturing industry. Methods A total of 740 employees from an electronic manufacturing enterprise were selected as the study subjects. According to the detection of occupational hazard factors, they were divided into noise group, noise benzene group, and noise dust group, with 325, 167, and 248 people, respectively. Occupational health examinations were conducted on the study participants to analyze their HFHL detection status and influencing factors. Results Among all participants (n=740), 456 (61.62%) were male, 284 (38.38%) were female, and 123 (15.62%) were detected with HFHL. The detection rate of HFHL increased with age and length of service (P<0.01). According to the exposure factor grouping, the detection rates of HFHL in the noise group, noise benzene group, and noise dust group were 12.00%, 19.16%, and 20.97%, respectively (P<0.05). Multivariate logistic regression analysis showed that workers aged ≥ 40 years, with 10-20 years of work experience, ≥ 20 years of work experience, exposure to noise and benzene series, and exposure to noise and dust had an increased risk of developing HFHL to 1.734, 1.923, 3.071, 1.706, and 1.527, respectively (P<0.05). Conclusion Combined exposure to noise and benzene series, combined exposure to noise and dust, as well as age and extended length of service may increase the risk of HFHL among workers.

Aim To investigate the antidepressant mechanism of hyperforin via the utilization of single-cell sequencing technology.Methods C57BL/6 mice were randomly divided into the control group,depres-sion model group,and hyperforin intervention group.The chronic unpredictable mild stress(CUMS)model was induced and drug interventions were administered for 28 d.Behavioral experiments were conducted to as-sess depressive symptoms,and hippocampal tissue was collected for single-cell RNA sequencing.Key cell populations and differentially expressed genes across groups were identified,followed by PPI network,GO,and KEGG enrichment analysis.Results Behavioral experiments indicated that CUMS successfully induced depressive symptoms in mice,while hyperforin im-proved depressive behavior.In the depression model group,the proportion of brain perivascular macrophages(PVM)increased,and this proportion decreased after hyperforin intervention,approaching the level seen in the control group.The top 20 common differentially ex-pressed genes in the PVM subpopulation were Saa3,Hbb-bs and Ccl24.PPI network analysis identified core targets,including Ccl2,Dhx9,C3,Msr1,Cxcl2 and Cx3cr1.KEGG enrichment analysis revealed pathways related to chemokines,phagosome formation,and inosi-tol phosphate metabolism.Conclusion The antide-pressant mechanism of hyperforin may be related to the regulation of Ccl24 and its related chemokine signaling pathway by PVM.

Aim To explore the mechanism of Con-grong Shujing granule(CSGs)in the treatment of Par-kinson's disease(PD)by network pharmacology,mo-lecular docking and parallel reaction monitoring(PRM)technology.Methods The active components of CSGs and the target genes of Parkinson's disease were obtained through the database.The intersection targets of drugs and diseases were selected to construct the"drug-active ingredient-target"and protein interac-tion network.The intersection target genes were impor-ted into David database for GO and KEGG enrichment analysis,and the main components were docked with key targets.27 SD rats were randomly divided into the normal group(n=9),model group(n=9)and treat-ment group(n=9).On day 1,7 and 14 of treatment,PRM analysis was used to detect the changes in the specific peptides of key target proteins in the substantia nigra of rats.Results The main components of CSGs wereTanshialdehyde,Baicalein,Quercetin and Kaempferol.The most important targets for the treat-ment of PD were TP53,AKT1,EGFR,HSP90 AA1 and STAT3.KEGG analysis mainly enriched MAPK,PI3K-Akt and neurotrophic factor signaling pathway.The molecular docking between core components and core targets showed that the binding of drugs and targets had good activity.PRM analysis of key proteins found that the target peptide expression levels of ASK1,JNK1 and JNK3 were different among groups(P＜0.05).Con-clusion CSGs can alleviate ERS,inhibit apoptosis and play a neural protective role through the ASK1-JNK pathway.

Objective:To develop a multi-parameter diagnostic model for pediatric McCune-Albright syndrome(MAS) using machine learning techniques based on laboratory data from MAS patients, with the goal of providing a rapid and reliable auxiliary diagnostic tool for clinical practice.Methods:In this retrospective study, 232 children diagnosed with MAS at the Department of Pediatrics, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from March 2023 to November 2024 were enrolled as the positive group. After removing duplicate or missing data, 119 cases were finally selected for statistical analysis as the positive group. Meanwhile, 113 children with normal physical examinations during the same period were selected as the control group. The clinical manifestations of the classic " triad" in the positive group were documented. Fasting serum samples were obtained from both groups at 8: 00 AM for laboratory testing, including bone metabolism-related and hormone-related indicators, which served as candidate features. Baseline descriptive analysis was conducted on the hormone-related indicators. For the bone metabolism indicators, six machine learning models—support vector machine(SVM), XGBoost, decision tree, random forest, Logistic regression, and K-nearest neighbor(KNN)—were constructed using R software. XGBoost subgroup analysis was performed based on the triad symptoms. The contribution of individual features to model predictions was visualized using SHAP diagrams. Results:SHAP visualization indicated that age, serum phosphorus, osteocalcin, and β-C-terminal cross-linked telopeptide of type Ⅰ collagen had the greatest average impact on model predictions. Among the six models, the SVM model achieved the highest diagnostic performance, with a sensitivity of 0.742 9, a specificity of 0.909 1, and an area under the curve (AUC) of 0.917.Conclusion:This study demonstrates that machine learning models, based on data from the positive patients and normal controls, can effectively distinguish MAS patients from healthy controls. The diagnostic model developed offers clinicians a valuable tool for early detection of MAS in children, contributing to earlier diagnosis, timely intervention, and improved clinical management.

McCune-Albright syndrome(MAS) is a postzygotic somatic mutation disorder caused by activating mutations in the GNAS gene, which encodes the α subunit of the stimulatory G protein. Its clinical features typically include polyostotic fibrous dysplasia, cafe-au-lait skin pigmentation, and endocrine hyperactivity, such as Cushing′s syndrome, hyperthyroidism, and growth hormone excess. Here, we report two rare cases of MAS complicated with adrenocorticotropic hormone(ACTH)-independent Cushing syndrome, and provide a review and analysis of previously reported MAS cases associated with Cushing′s syndrome.

Objective:To investigate the imaging characteristics of fibrous dysplasia(FD) in children with McCune-Albright syndrome(MAS) and the correlation between FD severity and bone metabolism markers, so as to provide a basis for clinical diagnosis and treatment.Methods:A total of 46 children(38 females and 8 males) with MAS with FD who were admitted to the Department of Pediatrics of Ruijin Hospital, Shanghai Jiao Tong University School of Medicine from January 2010 to December 2016 were included in the retrospective study, and all of them met the diagnostic criteria for either the MAS triad or dual manifestations. The extent and characteristics of FD lesions were evaluated by imaging analysis(X-ray and CT). The distribution of café-au-lait spots and endocrine abnormalities were recorded. The serum bone metabolism levels [total procollagen type 1 amino-terminal propeptide(TP1NP), osteocalcin, β-C-terminal telopeptide(β-CTX), alkaline phosphatase(ALP)], and other related indicators such as calcium, phosphorus, magnesium, and fibroblast growth factor(FGF23) levels were detected, and the association between FD severity and indicators was evaluated by Spearman correlation analysis.Results:Among the 46 children, there were 24 cases of triad(FD+ café-au-lait spots + precocious puberty) and 22 cases of dual manifestations(11 cases of FD+ café-au-lait spots or precocious puberty). The age of onset of FD patients(24 cases) with bilateral long bones and skull FD was significantly earlier than that in the unilateral FD group [(3.33±1.34)years vs(5.26±2.34)years, P<0.01], and all of them had extensive café-au-lait spots across the midline. Polyostotic FD accounted for 71.7%(33/46), mainly cystic expansive lesions involving the femur(30 cases) and tibia(24 cases), and skull FD(25 cases) mostly showed ground-glass changes; Monostotic FD(13 cases) was more common in the skull(5 cases) and phalanges(5 cases). FD severity was significantly positively correlated with ALP( ρ=0.554, P=0.002), and negatively correlated with serum phosphorus( ρ=-0.522, P=0.006). All 6 children with severe fractures had FGF23-mediated hypophosphatemia [(1.03±0.12) mmol/L vs control(1.52±0.15) mmol/L, P=0.003]. Conclusions:Extensive café-au-lait spots(across the midline) in children with MAS are strongly associated with early-onset polyostotic FD; FD severity was strongly associated with bone turnover markers(TP1NP, β-CTX, ALP) and FGF23-mediated hypophosphatemia. Early comprehensive skeletal assessment and regular FGF23 monitoring are recommended for children with MAS presenting with extensive cutaneous café-au-lait spots.

Anti-neutrophil cytoplasmic antibody-associated vasculitis (AAV) induced by anti-thyroid drugs has been reported occasionally, but methimazole-induced AAV is not as frequently reported. This case report described a 54-year-old male who developed AAV and multiple organ failure after more than 20 days of methimazole treatment. After timely discontinuation of the disease-causing drug methimazole, the patient received methylprednisolone shock, cyclophosphamide immunosuppression, renal replacement therapy, and other supportive treatments, and the disease was alleviated without recurrence.

Aim To investigate the antidepressant mechanism of hyperforin via the utilization of single-cell sequencing technology.Methods C57BL/6 mice were randomly divided into the control group,depres-sion model group,and hyperforin intervention group.The chronic unpredictable mild stress(CUMS)model was induced and drug interventions were administered for 28 d.Behavioral experiments were conducted to as-sess depressive symptoms,and hippocampal tissue was collected for single-cell RNA sequencing.Key cell populations and differentially expressed genes across groups were identified,followed by PPI network,GO,and KEGG enrichment analysis.Results Behavioral experiments indicated that CUMS successfully induced depressive symptoms in mice,while hyperforin im-proved depressive behavior.In the depression model group,the proportion of brain perivascular macrophages(PVM)increased,and this proportion decreased after hyperforin intervention,approaching the level seen in the control group.The top 20 common differentially ex-pressed genes in the PVM subpopulation were Saa3,Hbb-bs and Ccl24.PPI network analysis identified core targets,including Ccl2,Dhx9,C3,Msr1,Cxcl2 and Cx3cr1.KEGG enrichment analysis revealed pathways related to chemokines,phagosome formation,and inosi-tol phosphate metabolism.Conclusion The antide-pressant mechanism of hyperforin may be related to the regulation of Ccl24 and its related chemokine signaling pathway by PVM.