ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

Objective:To analyze the relationship between 24-hour urinary calcium (24 h UCa) level and the risk of end-stage kidney disease (ESKD), cardiovascular disease (CVD), and all-cause mortality.Methods:In the Chinese Cohort Study of Chronic Kidney Disease, we examined 3 375 patients aged 18-74 years with CKD stages 1-4. Kaplan-Meier survival and Cox proportional hazard regression models were used to test a time-to-event association between levels of 24 h UCa and incidence of ESKD, CVD, and all-cause mortality.Results:During a follow-up of 4.17 (3.37, 5.20) years, 179, 145, 104 and 38 ESKD events occurred in <0.60, 0.60-, 1.20-, ≥2.32 mmol 24 h UCa groups. Higher levels of 24 h UCa (1.20-,≥2.32 mmol) were independently associated with a lower incidence of ESKD events in patients with CKD, with HR (95% CI) of 0.71 (0.54-0.93) and 0.43 (0.29-0.64), respectively. No significant associations with CVD and all-cause mortality endpoints were detected. Conclusion:Among patients with CKD, levels of 24 h UCa displayed an association with the risk of ESKD among patients with CKD stages 1-4.

Objective To investigate the electroencephalography(EEG)signal characteristics in patients with neuropathic pain(NP)associated with spinal cord injury(SCI).Methods A total of 90 patients with SCI from January,2018 to November,2023 were selected from the EEG database of the Department of Rehabilitation Medicine,Xijing Hospital,and divided into NP group(n=46)and non-NP group(n=44)according to their symptoms.The resting-state EEG power and reactivity to eye-opening were compared between two groups.Results Compared with non-NP group,EEG power increased in frontal lobe in α and β1 bands,central lobe in δ,θ,α1 and β1 bands,parietal lobe in α and β1 bands,temporal lobe in α and β1 bands,left occipital lobe in α2 band,and occipital lobe in α1 and β1 bands(|Z|>1.998,P<0.05)in NP group during eye-opening;during eye-closing,EEG power increased in prefrontal lobe in α1 and β1 bands,right frontal lobe in θ band,frontal lobe in α and β1 bands,left frontal lobe in β2 band,central lobe in δ,α1 and β1 bands,parietal lobe in α1 and β1 bands,left pari-etal lobe in α2 and β2 bands,right temporal lobe in θ band,temporal lobe in α and β bands,occipital lobe in α1 and β1 bands,and left occipital lobe in β2 band(|Z|>1.970,P<0.05);while the reactivity to eye-opening de-creased in right prefrontal lobe in β1 band,frontal lobe in θ,α and β bands,right central lobe in β1 band,parietal lobe in α1 and β1 bands,right parietal lobe in β2 band,right temporal lobe in δ and θ band,temporal lobe in α1 and β bands,left occipital lobe in α1 band,and occipital lobe in β1(|Z|>1.967,P<0.05).Conclusion Resting-state EEG power characteristically elevates in NP patients after SCI,and the reactivity to eye-open-ing reduces.

Objective To investigate the clinical characteristics and prognostic risk factors in elderly patients with acute myeloid leukemia(AML).Methods A retrospective analysis was conducted on the clinical data of 101 elderly AML patients admitted to Affiliated Hospital of Jiaxing University from January 2022 to December 2024.All patients were treated with azacitidine+venetoclax regimen.The clinical characteristics of patients and the risk factors related to prognosis were explored.Results The median follow-up was 14 months.Among the 101 patients,74 achieved complete remission or complete remission with incomplete hematological recovery.The median overall survival(OS)of patients with aged ≥70 years,white blood cell count＞50 × 109/L,TP53 mutation,complex chromosomes,and high-risk European leukemia net(ELN)risk stratification was significantly shortened(P＜0.05).Multivariate analysis showed that age(HR=0.125,95％CI:0.023-0.662,P=0.015),white blood cell count(HR=0.145,95％CI:0.032-0.662,P=0.013),and ELN risk stratification(HR=100.397,95％CI:14.395-700.207,P＜0.001)were all independent influencing factors for OS in elderly AML patients.Conclusion Age,white blood cell count and ELN risk stratification are all independent influencing factors affecting OS in elderly AML patients.

Acute symptomatic osteoporotic thoracolumbar compression fracture (ASOTLF) can lead to chronic low back pain, kyphosis deformity, pulmonary dysfunction, loss of mobility, and even life-threatening complications. Vertebral augmentation is currently the mainstream treatment method for this condition. In 2019, the Editorial Board of Chinese Journal of Trauma and the Spinal Trauma Group of Orthopedic Surgeons Branch of Chinese Medical Doctor Association collaboratively led the development of Clinical guideline for vertebral augmentation for acute symptomatic osteoporotic thoracolumbar compression fractures. Six years later, with advances in clinical diagnosis and treatment techniques as well as accumulating evidence in related fields, the 2019 guideline requires updating. To this end, the Spinal Trauma Group of Orthopedic Surgeons Branch of Chinese Medical Doctor Association, the Spinal Health Professional Committee of China Human Health Science and Technology Promotion Association, and the Minimally Invasive Orthopedics Professional Committee of Shaanxi Medical Doctor Association have organized experts in the field to develop the Clinical guideline for vertebral augmentation of acute symptomatic osteoporotic thoracolumbar compression fractures ( version 2025) , based on the latest evidence-based medical researches. This guideline incorporates 3 recommendations retained from the 2019 version with updated strength of evidence, along with 12 new recommendations. It provides recommendations from six aspects of diagnosis, pain management, treatment option selection, prevention of postoperative complications, anti-osteoporosis therapy, and postoperative rehabilitation, aiming to provide a reference for standard treatment of vertebral augmentation for ASOTLF in hospitals at all levels.

Objective:To relate the changes in electroencephalography (EEG) signals after a spinal cord injury (SCI) with functional independence.Methods:The EEG data describing ninety SCI patients in both open and closed eye states were compared with those collected from 45 healthy counterparts. The SCI patients′ EEG data were correlated with their spinal cord independence measure (SCIM) scores at corresponding time points. The SCI patients were divided into a cervical SCI group (SCI-C group) and a non-cervical SCI group (SCI-NC group), with 45 cases in each group. The difference in EEG data between them and its correlation with the SCIM scores were also compared and analyzed.Results:In the eyes-open state, the EEG power in the frontal, central, temporal, and right occipital regions of the SCI group was lower than among the control group, on average. There were significant differences in the δ and θ low-frequency bands. The α1 band power in the frontal and right parietal regions was significantly higher in the SCI group, on average. With the eyes closed the δ band power in the right prefrontal, frontal, left central, and temporal regions of the SCI group was lower than among the control group, while the α1 band power in the right prefrontal, frontal, central, and parietal regions was significantly higher. The reactivity to eye opening of the α1 band in the right prefrontal, frontal, central, parietal, and temporal regions was less in the SCI patients compared to healthy subjects. Among the SCI patients, higher EEG power in the β2 band of the right frontal lobe and the α2 and β bands of the right temporal lobe was significantly positively correlated with higher SCIM scores during the eyes-open measurements. And the higher EEG power in the α2 band of the prefrontal and frontal lobes, the β2 band of the frontal lobe, the α2 band of the right central region, the α2 and β bands of the temporal lobe, and the α2 and β2 bands of the occipital lobe was significantly positively correlated with higher SCIM scores during the eyes-closed state. The subgroup analysis showed that the δ band power in the left temporal lobe and the α2 band power in the parietal lobe were lower among the SCI-C compared with the SCI-NC patients in the eyes-open state. With the eyes closed, the δ band power in the left frontal, left parietal, and left temporal lobes and the α2 band power in the frontal, central, parietal, temporal, and right occipital lobes was significantly lower in the SCI-C group compared to the SCI-NC group, on average. The reactivity to eye opening of the δ band in the temporal lobe, the α2 band in the left prefrontal, frontal, central, parietal, temporal, and right occipital lobes, and the β2 band in the right parietal and left occipital lobes was less in the SCI-C group than in the SCI-NC group ( P≤0.05). Among the SCI-C patients, higher EEG power in the β1 and β2 bands of the right temporal lobe with the eyes open was significantly positively correlated with higher SCIM scores. With the eyes closed, higher EEG power in the α2 and β1 bands of the right prefrontal lobe was significantly positively correlated with higher SCIM scores. Among the SCI-NC patients, higher EEG power in the δ band of the prefrontal lobe, the β1 and β2 bands of the left prefrontal lobe, and the δ bands of the frontal, central, right parietal, and right temporal lobes during the eyes open measurements was significantly positively correlated with higher SCIM scores. Conclusions:The EEG power of cervical and non-cervical SCI patients shows characteristic changes which correlate with their functional independence.

Objective:To analyze the relationship between 24-hour urinary calcium (24 h UCa) level and the risk of end-stage kidney disease (ESKD), cardiovascular disease (CVD), and all-cause mortality.Methods:In the Chinese Cohort Study of Chronic Kidney Disease, we examined 3 375 patients aged 18-74 years with CKD stages 1-4. Kaplan-Meier survival and Cox proportional hazard regression models were used to test a time-to-event association between levels of 24 h UCa and incidence of ESKD, CVD, and all-cause mortality.Results:During a follow-up of 4.17 (3.37, 5.20) years, 179, 145, 104 and 38 ESKD events occurred in <0.60, 0.60-, 1.20-, ≥2.32 mmol 24 h UCa groups. Higher levels of 24 h UCa (1.20-,≥2.32 mmol) were independently associated with a lower incidence of ESKD events in patients with CKD, with HR (95% CI) of 0.71 (0.54-0.93) and 0.43 (0.29-0.64), respectively. No significant associations with CVD and all-cause mortality endpoints were detected. Conclusion:Among patients with CKD, levels of 24 h UCa displayed an association with the risk of ESKD among patients with CKD stages 1-4.

Exercise-induced metabolic remodeling is a fundamental adaptive process whereby the body reorganizes systemic and cellular metabolism to meet the dynamic energy demands posed by physical activity. Emerging evidence reveals that such remodeling not only enhances energy homeostasis but also profoundly influences immune function through complex molecular interactions involving glucose, lipid, and protein metabolism. This review presents an in-depth synthesis of recent advances, elucidating how exercise modulates immune regulation via metabolic reprogramming, highlighting key molecular mechanisms, immune-metabolic signaling axes, and the authors’ academic perspective on the integrated “exercise-metabolism-immunity” network. In the domain of glucose metabolism, regular exercise improves insulin sensitivity and reduces hyperglycemia, thereby attenuating glucose toxicity-induced immune dysfunction. It suppresses the formation of advanced glycation end-products (AGEs) and interrupts the AGEs-RAGE-inflammation positive feedback loop in innate and adaptive immune cells. Importantly, exercise-induced lactate, traditionally viewed as a metabolic byproduct, is now recognized as an active immunomodulatory molecule. At high concentrations, lactate can suppress immune function through pH-mediated effects and GPR81 receptor activation. At physiological levels, it supports regulatory T cell survival, promotes macrophage M2 polarization, and modulates gene expression via histone lactylation. Additionally, key metabolic regulators such as AMPK and mTOR coordinate immune cell energy balance and phenotype; exercise activates the AMPK-mTOR axis to favor anti-inflammatory immune cell profiles. Simultaneously, hypoxia-inducible factor-1α (HIF-1α) is transiently activated during exercise, driving glycolytic reprogramming in T cells and macrophages, and shaping the immune landscape. In lipid metabolism, exercise alleviates adipose tissue inflammation by reducing fat mass and reshaping the immune microenvironment. It promotes the polarization of adipose tissue macrophages from a pro-inflammatory M1 phenotype to an anti-inflammatory M2 phenotype. Moreover, exercise alters the secretion profile of adipokines—raising adiponectin levels while reducing leptin and resistin—thereby influencing systemic immune balance. At the circulatory level, exercise improves lipid profiles by lowering pro-inflammatory free fatty acids (particularly saturated fatty acids) and triglycerides, while enhancing high-density lipoprotein (HDL) function, which has immunoregulatory properties such as endotoxin neutralization and macrophage cholesterol efflux. Regarding protein metabolism, exercise triggers the expression of heat shock proteins (HSPs) that act as intracellular chaperones and extracellular immune signals. Exercise also promotes the secretion of myokines (e.g., IL-6, IL-15, irisin, FGF21) from skeletal muscle, which modulate immune responses, facilitate T cell and macrophage function, and support immunological memory. Furthermore, exercise reshapes amino acid metabolism, particularly of glutamine, arginine, and branched-chain amino acids (BCAAs), thereby influencing immune cell proliferation, biosynthesis, and signaling. Leucine-mTORC1 signaling plays a key role in T cell fate, while arginine metabolism governs macrophage polarization and T cell activation. In summary, this review underscores the complex, bidirectional relationship between exercise and immune function, orchestrated through metabolic remodeling. Future research should focus on causative links among specific metabolites, signaling pathways, and immune phenotypes, as well as explore the epigenetic consequences of exercise-induced metabolic shifts. This integrated perspective advances understanding of exercise as a non-pharmacological intervention for immune regulation and offers theoretical foundations for individualized exercise prescriptions in health and disease contexts.