1.Volatile Component Differences in Xihuangwan Prepared with Natural and Artificial Musk Based on Non-targeted and Targeted Metabolomics
Jing WANG ; Fangzhu XU ; Li MENG ; Qizhen ZHU ; Huanjun ZHAO ; Caina YU ; Xuelian CHEN ; Hui GAO ; Zimin YUAN
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(8):194-201
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.
2.Volatile Component Differences in Xihuangwan Prepared with Natural and Artificial Musk Based on Non-targeted and Targeted Metabolomics
Jing WANG ; Fangzhu XU ; Li MENG ; Qizhen ZHU ; Huanjun ZHAO ; Caina YU ; Xuelian CHEN ; Hui GAO ; Zimin YUAN
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(8):194-201
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.
3.Epidemiological survey of Helicobacter pylori infection and correlation of dietary and lifestyle habits among adult physical examination population in Xuzhou Area
Jiao JIAO ; Xingsong JIANG ; Chunping QIAN ; Shujuan GAO ; Shuli ZHAO ; Jie ZHUANG ; Hui ZHANG ; Yun ZHU
Journal of Public Health and Preventive Medicine 2026;37(1):163-166
Objective To explore the prevalence of Helicobacter pylori (Hp) infection and its association with dietary and lifestyle habits among the adult physical examination population in Xuzhou area. Methods Retrospectively selected the physical examination population who underwent HP testing at our hospital's physical examination center from May 2021 to December 2023 as the research object. The prevalence of Hp infection in the population was analyzed based on the physical examination results. A questionnaire survey was used to collect information on the eating and living habits of all study subjects. Logistic regression was used to analyze the relationship between eating and living habits and Hp infection. Results A total of 1 354 physical examination people were included in the study, and the Hp infection rate was 37.30% (505/1354). The difference in Hp infection rates among people of different age groups is statistically significant (P<0.05), with the middle-aged population (41-59 years old) having the highest Hp positive infection rate (45.38%).High salt (41.11%), hot diet (40.56%), history of smoking (45.23%) and drinking (43.80%), less consumption of fruits and vegetables (43.73%), irregular exercise (41.29%), irregular diet People who frequently eat out (43.56%) and eat out frequently (42.57%) have a higher Hp infection rate (P<0.05).After adjusting for demographic factors such as gender, age, place of residence and education level, multivariate Logistic regression results showed that high-salt diet (OR=3.975, 95%CI: 2.670-5.917) and hot diet (OR=3.357, 95%CI: 2.291-4.919), smoking (OR=1.458, 95%CI: 1.082-1.964), drinking alcohol (OR=1.654, 95%CI: 1.279-2.138), eating fruits and vegetables (OR=1.759, 95%CI: 1.345-2.301), regular exercise (OR=1.822, 95%CI: 1.371-2.421), regular diet (OR=1.893, 95%CI: 1.391-2.575), eating out (OR=1.690, 95%CI: 1.277-2.237) were associated with the risk of Hp infection (P<0.05). Conclusion The positive infection rate of Hp among the physical examination population in Xuzhou is slightly lower than the average epidemic level in China. Cultivating healthy eating and living habits can effectively reduce the risk of Hp infection.
4.Analysis of potentially inappropriate medication and influencing factors among the elderly in six nursing homes in Urumqi
Qianhui LI ; Jianhua WANG ; Shangjie YANG ; Biao WU ; Lina ZHU ; Dongling PENG ; Hui GAO ; Chunlin LUO ; Zhanlei QIN ; Eli GULMIRA ; Ningning WANG ; Aierken AIZEZIJIANG ; Yubo WANG
China Pharmacy 2026;37(12):1614-1620
OBJECTIVE To investigate the prevalence and influencing factors of potentially inappropriate medication (PIM) among the elderly in nursing homes in Urumqi based on three PIM screening tools, and to compare the applicability of different tools. METHODS A cross-sectional study design was adopted. Elderly individuals from six nursing homes in Urumqi were selected as the research subjects from May 2021 to September 2023. Demographic characteristics, disease burden and medication records of the elderly were collected. PIM screening was performed using the Chinese PIM criteria (2024 edition), the American Geriatrics Society (AGS) Beers criteria (2023 edition), and the Screening Tool of Older Person’S Prescriptions(STOPP)/Screening Tool to Alert to Right Treatment(START) (2023 edition). Fleiss’s Kappa test was used to assess the consistency among the three screening tools, and multivariate Logistic regression was used to analyze the influencing factors of PIM. RESULTS The prevalence of PIM screened by the Chinese PIM criteria was 47.4% (323/682), by the AGS Beers criteria was 43.4% (296/682), and by the STOPP criteria was 50.9% (347/682). The consistency among the three screening tools was low (Fleiss’s Kappa=0.12, P <0.001). Multivariate Logistic regression analysis showed that all three screening tools indicated that polypharmacy, aspirin use and psychotropic drug use were independent risk factors for PIM among elderly in nursing houses (all OR>1, P <0.05). CONCLUSIONS The prevalence of PIM among the elderly in nursing homes in Urumqi is relatively high. Polypharmacy, aspirin use and psychotropic drug use are common independent risk factors for PIM. There are differences in screening results among the three tools with low consistency. The Chinese PIM criteria can serve as a first-line tool for PIM screening in nursing homes.
5.Regulation of Immune Function by Exercise-induced Metabolic Remodeling
Hui-Guo WANG ; Gao-Yuan YANG ; Xian-Yan XIE ; Yu WANG ; Zi-Yan LI ; Lin ZHU
Progress in Biochemistry and Biophysics 2025;52(6):1574-1586
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.
6.Identification of core genes of osteoarthritis by bioinformatics
Xuekun ZHU ; Heng LIU ; Hui FENG ; Yunlong GAO ; Lei WEN ; Xiaosong CAI ; Ben ZHAO ; Min ZHONG
Chinese Journal of Tissue Engineering Research 2025;29(3):637-644
BACKGROUND:At present,osteoarthritis has become a major disease affecting the quality of life of the elderly,and the therapeutic effect is poor,often focusing on preventing the disease process,and the pathogenesis of osteoarthritis is still not fully understood.Bioinformatics analysis was carried out to explore the main pathogenesis of osteoarthritis and related mechanisms of gene coding regulation. OBJECTIVE:To screen core differential genes with a major role in osteoarthritis by gene expression profiling. METHODS:Datasets were downloaded from the Gene Expression Omnibus(GEO):GSE114007,GSE117999,and GSE129147.Differential genes in the GSE114007 and GSE117999 data collections were screened using R software,performing differential genes to weighted gene co-expression network analysis.The module genes most relevant to osteoarthritis were selected to perform protein interaction analysis.Candidate core genes were selected using the cytocape software.The candidate core genes were subsequently subjected to least absolute shrinkage and selection operator regression and COX analysis to identify the core genes with a key role in osteoarthritis.The accuracy of the core genes was validated using an external dataset,GSE129147. RESULTS AND CONCLUSION:(1)A total of 477 differential genes were identified,265 differential genes associated with osteoarthritis were obtained by weighted gene co-expression network analysis,and 8 candidate core genes were identified.The least absolute shrinkage and selection operator regression analysis finally yielded a differential gene ASPM with core value that was externally validated.(2)It is concluded that abnormal gene ASPM expression screened by bioinformatics plays a key central role in osteoarthritis.
7.Prognostic value of quantitative flow ratio measured immediately after percutaneous coronary intervention for chronic total occlusion.
Zheng QIAO ; Zhang-Yu LIN ; Qian-Qian LIU ; Rui ZHANG ; Chang-Dong GUAN ; Sheng YUAN ; Tong-Qiang ZOU ; Xiao-Hui BIAN ; Li-Hua XIE ; Cheng-Gang ZHU ; Hao-Yu WANG ; Guo-Feng GAO ; Ke-Fei DOU
Journal of Geriatric Cardiology 2025;22(4):433-442
BACKGROUND:
The clinical impact of post-percutaneous coronary intervention (PCI) quantitative flow ratio (QFR) in patients treated with PCI for chronic total occlusion (CTO) was still undetermined.
METHODS:
All CTO vessels treated with successful anatomical PCI in patients from PANDA III trial were retrospectively measured for post-PCI QFR. The primary outcome was 2-year vessel-oriented composite endpoints (VOCEs, composite of target vessel-related cardiac death, target vessel-related myocardial infarction, and ischemia-driven target vessel revascularization). Receiver operator characteristic curve analysis was conducted to identify optimal cutoff value of post-PCI QFR for predicting the 2-year VOCEs, and all vessels were stratified by this optimal cutoff value. Cox proportional hazards models were employed to calculate the hazard ratio (HR) with 95% CI.
RESULTS:
Among 428 CTO vessels treated with PCI, 353 vessels (82.5%) were analyzable for post-PCI QFR. 31 VOCEs (8.7%) occurred at 2 years. Mean value of post-PCI QFR was 0.92 ± 0.13. Receiver operator characteristic curve analysis shown the optimal cutoff value of post-PCI QFR for predicting 2-year VOCEs was 0.91. The incidence of 2-year VOCEs in the vessel with post-PCI QFR < 0.91 (n = 91) was significantly higher compared with the vessels with post-PCI QFR ≥ 0.91 (n = 262) (22.0% vs. 4.2%, HR = 4.98, 95% CI: 2.32-10.70).
CONCLUSIONS
Higher post-PCI QFR values were associated with improved prognosis in the PCI practice for coronary CTO. Achieving functionally optimal PCI results (post-PCI QFR value ≥ 0.91) tends to get better prognosis for patients with CTO lesions.
8.Glucocorticoid Discontinuation in Patients with Rheumatoid Arthritis under Background of Chinese Medicine: Challenges and Potentials Coexist.
Chuan-Hui YAO ; Chi ZHANG ; Meng-Ge SONG ; Cong-Min XIA ; Tian CHANG ; Xie-Li MA ; Wei-Xiang LIU ; Zi-Xia LIU ; Jia-Meng LIU ; Xiao-Po TANG ; Ying LIU ; Jian LIU ; Jiang-Yun PENG ; Dong-Yi HE ; Qing-Chun HUANG ; Ming-Li GAO ; Jian-Ping YU ; Wei LIU ; Jian-Yong ZHANG ; Yue-Lan ZHU ; Xiu-Juan HOU ; Hai-Dong WANG ; Yong-Fei FANG ; Yue WANG ; Yin SU ; Xin-Ping TIAN ; Ai-Ping LYU ; Xun GONG ; Quan JIANG
Chinese journal of integrative medicine 2025;31(7):581-589
OBJECTIVE:
To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM).
METHODS:
This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis.
RESULTS:
Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings.
CONCLUSIONS
RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult
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Aged
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Female
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Humans
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Male
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Middle Aged
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Arthritis, Rheumatoid/drug therapy*
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Glucocorticoids/therapeutic use*
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Medicine, Chinese Traditional
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Retrospective Studies
9.Correlation between dynamic contrast-enhanced MRI imaging and clinical pathological features of invasive breast cancer and lymphovascular invasion
Shi-Qi GUO ; Yu-Jiao XIE ; Qing-Yang LI ; Si-Yi CHEN ; Jia-Hong SUN ; Zhao-Feng GAO ; Jun-Qing LIANG ; Yu-Hui CHEN ; Bao-Shi BAO ; Li ZHU ; Jian-Dong WANG
Medical Journal of Chinese People's Liberation Army 2025;50(7):847-854
Objective To explore the relationship between dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)and clinical pathological features of invasive breast cancer and lymphovascular invasion(LVI).Methods Imaging and clinical pathological data were retrospectively collected from 508 patients with invasive breast cancer who underwent breast DCE-MRI at the First Medical Center of Chinese PLA General Hospital from January 2019 to August 2021.Patients were divided into the LVI-positive(LVI+)group(n=79)and LVI-negative(LVI-)group(n=429)based on postoperative pathological results.Univariate and multivariate logistic regression analyses were used to identify risk factors for LVI.Results Compared with LVI-group,LVI+group had a higher proportion of patients aged<45 years(44.3%vs.27.0%,P=0.002),non-mass-like enhancement(NME)(31.7%vs.17.7%,P=0.004),Ki-67 expression rate(40.0%vs.30.0%,P<0.001),high Ki-67 expression(94.9%vs.78.1%,P=0.001),Luminal B subtype(76.0%vs.60.1%,P=0.008),and positive axillary lymph nodes rate(72.2%vs.31.5%,P<0.001),while the proportion of Luminal A subtype was lower(2.5%vs.21.5%,P<0.001).Univariate and multivariate logistic regression analyses showed that age≥45 years(OR=0.468,95%CI 0.280-0.783,P=0.004)was an independent protective factor for LVI,while NME(OR=1.987,95%CI 1.126-3.444,P=0.016)was an independent risk factor.Compared with Luminal A subtype,patients with Luminal B subtype(OR=10.482,95%CI 3.164-64.923,P=0.001),HER-2 overexpression subtype(OR=11.571,95%CI 2.755-79.341,P=0.003)and triple-negative subtypes(OR=8.433,95%CI 1.985-57.908,P=0.009)had a higher risk of LVI.Conclusions Age≥45 years is an independent protective factor for LVI,while NME is an independent risk factor.Among molecular subtypes,patients with Luminal B,HER-2 overexpression and triple-negative subtypes have a higher risk of LVI compared with the Luminal A subtype.
10.Genome-wide DNA methylation and mRNA transcription analysis revealed aberrant gene regulation pathways in patients with dermatomyositis and polymyositis.
Hui LUO ; Honglin ZHU ; Ding BAO ; Yizhi XIAO ; Bin ZHOU ; Gong XIAO ; Lihua ZHANG ; Siming GAO ; Liya LI ; Yangtengyu LIU ; Di LIU ; Junjiao WU ; Qiming MENG ; Meng MENG ; Tao CHEN ; Xiaoxia ZUO ; Quanzhen LI ; Huali ZHANG
Chinese Medical Journal 2025;138(1):120-122


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