1.Salidroside inhibits osteoclast differentiation based on osteoblast-osteoclast interaction via HIF-1a pathway.
Yutong JIN ; Yao WANG ; Chuan WANG ; Lingling ZHANG ; Dandan GAO ; Haizhao LIU ; Qingwen CAO ; Chenchen TIAN ; Yuhong BIAN ; Yue WANG
Chinese Journal of Natural Medicines (English Ed.) 2025;23(5):572-584
This study investigated the regulatory potential of salidroside (SAL), a primary active compound in Rhodiola rosea L., on osteoclast differentiation by modulating the hypoxia-inducible factor 1-alpha (HIF-1a) pathway in osteoblasts. Luciferase reporter assay and chromatin immunoprecipitation (ChIP) assay were employed to validate whether the receptor activator of nuclear factor-?B ligand (RANKL) is the downstream target gene of HIF-1a in osteoblasts. The study also utilized lipopolysaccharide (LPS)-induced mouse osteolysis to examine the impact of SAL on osteolysis in vivo. Furthermore, conditioned medium (CM) from SAL-pretreated osteoblasts was used to investigate the paracrine effects on osteoclastogenesis through the HIF-1a pathway. Hypoxic condition-induced overexpression of HIF-1a upregulated RANKL levels by binding to the RANKL promoter and enhancing transcription in osteoblastic cells. In vivo, SAL significantly alleviated bone tissue hypoxia and decreased the expression of HIF-1a by downregulating the expression of RANKL, vascular endothelial growth factor (VEGF), interleukin 6 (IL-6), and angiopoietin-like 4 (ANGPTL4). In the paracrine experiment, conditioned media from SAL-pretreated osteoblasts inhibited differentiation through the HIF-1a/RANKL, VEGF, IL-6, and ANGPTL4 pathways. RANKL emerges as the downstream target gene regulated by HIF-1a in osteoblasts. SAL significantly alleviates bone tissue hypoxia and bone loss in LPS-induced osteolysis through the HIF-1a/RANKL, VEGF, IL-6, and ANGPTL4 pathways. SAL inhibits osteoclast differentiation by regulating osteoblast paracrine secretion.
Animals
;
Osteoblasts/cytology*
;
Hypoxia-Inducible Factor 1, alpha Subunit/genetics*
;
Glucosides/administration & dosage*
;
Cell Differentiation/drug effects*
;
Phenols/administration & dosage*
;
Mice
;
Osteoclasts/metabolism*
;
RANK Ligand/genetics*
;
Rhodiola/chemistry*
;
Osteogenesis/drug effects*
;
Signal Transduction/drug effects*
;
Interleukin-6/genetics*
;
Male
;
RAW 264.7 Cells
;
Osteolysis/genetics*
;
Humans
;
Mice, Inbred C57BL
2.Effect of Acupuncture Combined with Bloodletting and Cupping on the Expression of Coagulation-Complement-Mast Cell Activation Axis-Related Factors in Patients with Chronic Spontaneous Urticaria:Randomize-controlled Study
Yuzhu DU ; Yuqiang XUE ; Xiang LIU ; Yu SHI ; Hongkun LI ; Wenshan LIU ; Zan TIAN ; Yutong HU ; Yanjun WANG
Journal of Traditional Chinese Medicine 2025;66(2):150-156
ObjectiveTo observe the clinical efficacy of acupuncture combined with bloodletting and cupping in the treatment of chronic spontaneous urticaria(CSU) and to explore its potential mechanisms of action. MethodsSeventy CSU patients were randomly divided into loratadine group and acupuncture + bloodletting group, with 35 patients in each group. The loratadine group received oral loratadine tablets, 10 mg once daily in the evening. The acupuncture + bloodletting group received acupuncture at Zhongwan (CV 12), Guanyuan (CV 4), Tianshu (ST 25), Zusanli (ST 36), Sanyinjiao (SP 6), Xuehai (SP 10), Quchi (LI 11), Hegu (LI 4), Taichong (LR 3), Baihui (GV 20), and Shenting (GV 24), once daily,along with bloodletting and cupping at Dazhui (GV 14) and Geshu (BL 17), every other day. Both groups were treated for 4 weeks. The 7-day urticaria activity score(UAS7) was assessed before and after the treatment, and levels of serum immunoglobulin E (IgE), interleukin-4 (IL-4), interleukin-5 (IL-5), eosinophil cationic protein (ECP), plasma tissue factor (TF), activated factor Ⅶ (FⅦa), prothrombin fragment 1+2 (F1+2), D-dimer (D-D) and complement component 5a (C5a) were detected. ResultsA total of 65 patients were included in the final analysis, 32 in the loratadine group and 33 in the acupuncture + bloodletting group. Before treatment, there was no significant difference in UAS7 score, serum IgE, IL-4, IL-5, ECP levels, or plasma TF, FⅦa, F1+2, D-D, C5a levels between groups (P> 0.05). After treatment, both groups showed significant reductions in UAS7 score, serum IgE, IL-4, IL-5, and plasma TF, FⅦa, F1+2, D-D, and C5a levels compared to those before treatment (P<0.01). However, after treatment, there was no significant difference in UAS7 score and serum ECP, IgE, IL-4, IL-5 levels between groups (P>0.05). The acupuncture + bloodletting group showed lower plasma TF, FⅦa, F1+2, D-D and C5a levels compared to the loratadine group (P<0.05 or P<0.01). ConclusionAcupuncture combined with bloodletting and cupping can effectively improve the skin symptoms of CSU patients and reduce the levels of inflammatory factors. The potential mechanism of action may involve the regulation of the coagulation-complement-mast cell activation axis, thereby inhibiting mast cell degranulation.
3.A nomogram model based on serological indicators for predicting in-hospital major adverse cardiovascular events in elderly patients with acute coronary syndrome
Xiang ZHOU ; Ruihan LIU ; Yutong LIU ; Fan TIAN ; Jie ZHANG ; Xiaomao WANG ; Jian CAO
Chinese Journal of Geriatrics 2025;44(3):289-296
Objective:To develop a nomogram model utilizing serological indicators for predicting in-hospital major adverse cardiovascular events(MACE)in elderly patients diagnosed with acute coronary syndrome(ACS).Methods:This study involved a retrospective analysis of clinical data from 1, 818 elderly patients with ACS who were treated at the First Medical Center of the General Hospital of the People's Liberation Army from January 2022 to May 2024.The patients were randomly assigned to a training set(1, 272 cases)and a validation set(546 cases)in a 7: 3 ratio.Following a comparison of the two groups, the training set was further categorized into non-MACE and MACE groups based on the occurrence of endpoint events.Univariate analysis, Lasso regression, and multivariate logistic regression analyses were sequentially employed to identify factors influencing in-hospital MACE and to construct the nomogram model.The performance of the model was assessed using receiver operating characteristic(ROC)curves, calibration curves, and decision curves.Results:Among the 1, 818 ACS patients, the mean age was 67 years(interquartile range: 61.0 to 73.0), with 70.4% being male.Almost all indicators(except platelet count)exhibited no statistically significant differences between the training and validation sets(all P>0.05).However, statistically significant differences(all P<0.05)were observed in age, body mass index, neutrophil count, lymphocyte count, monocyte count, white blood cell count, hemoglobin, red blood cell distribution width, mean platelet volume, C-reactive protein(CRP), fibrinogen, D-dimer, albumin, direct bilirubin, troponin T(TnT), fasting blood glucose(FBG), estimated glomerular filtration rate(eGFR), uric acid, N-terminal pro-B-type natriuretic peptide(NT-proBNP), glycated hemoglobin(HbA1c), and high-density lipoprotein cholesterol(HDL-C)between the non-MACE and MACE groups in the training set.Ultimately, seven variables—neutrophil count, hemoglobin, red blood cell distribution width, CRP, TnT, FBG, and NT-proBNP—were selected to construct the nomogram model.The model demonstrated high discrimination in both the training and validation sets, with an area under the curve of 0.86(95% CI: 0.82-0.90)for the training set and 0.85(95% CI: 0.81-0.90)for the validation set.Furthermore, the calibration curves for both cohorts indicated a close agreement between predicted and actual risk estimates, suggesting improved model calibration.Decision curve analysis indicated that the predictive model has notable clinical utility. Conclusions:The constructed nomogram enhances the accuracy of predicting in-hospital MACE in elderly patients with ACS, thereby offering a valuable reference for clinical practice.
4.Research progress on big-data-driven analysis strategies for imbalanced data of rare events
Jiangjie ZHOU ; Yutong WANG ; Tian FENG ; Xianglong MENG ; Baosheng LIANG ; Shengfeng WANG
Chinese Journal of Pharmacoepidemiology 2025;34(8):952-961
Rare events are widely prevalent in various disciplines,including rare adverse reactions to vaccines and drugs,clinical rare diseases,and low-probability clinical outcomes.The reason for research interest on such events is that their occurrence often brings incalculable and serious consequences.In the context of big data,numerous methods have emerged for rare event data analysis,including sampling based,category weighting,ensemble learning,and deep learning.This article systematically summarizes the research progress of current rare event data analysis methods,and introduces their basic principles and applicable scenarios.By analyzing the advantages and disadvantages of existing methods,the challenges of rare event research are sorted out and summarized,and potential research directions in related fields are explored to provide references for researchers.
5.Correlation between triglyceride glucose index and prognosis in elderly patients with unstable angina
Xiang ZHOU ; Ruihan LIU ; Yutong LIU ; Fan TIAN ; Jie ZHANG ; Xiaomao WANG ; Jian CAO
Chinese Journal of Geriatric Heart Brain and Vessel Diseases 2025;27(2):136-139
Objective To explore the correlation between triglyceride glucose(TyG)index and per-cutaneous coronary intervention(PCI)following drug treatment in elderly patients with unstable angina pectoris(UAP).Methods A total of 221 elderly UAP patients admitted to the Hyperbaric Oxygen Department of the First Medical Center of Chinese PLA General Hospital from March 2016 to March 2024 were enrolled,and based on the tertiles of the TyG index,they were divided into low,medium and high TyG index groups(the index:≤8.48,8.49-8.92,>8.92;with 74,74 and 73 cases,respectively).Clinical data of all patients were collected,and whether undergoing PCI after discharge was defined as the endpoint event.The follow-up ended on May 10,2024.The clini-cal data were compared in the three groups.Kaplan-Meier survival curves were plotted to compare the survival rates among the groups,and Cox proportional hazards regression model was em-ployed to analyze the influencing factors for occurrence of endpoint event.Results There were significant differences in the three groups in terms of TyG index,BMI,diabetes,FPG,TC,TG,LDL-C,HDL-C,HbA1c,NT-proBNP,and incidence of endpoint event(P<0.05,P<0.01).Univa-riate Cox proportional hazards regression analysis showed that the TyG index,diabetes,and HbA1c were risk factors for endpoint events in elderly patients with UAP(HR=2.523,95%CI:1.593-3.996;HR=2.543,95%CI:1.263-5.118;HR=1.434,95%CI:1.159-1.774).Further multivariate Cox proportional hazards regression analysis showed that,after adjusting for diabetes and HbA1c,the TyG index was an independent risk factor for PCI after discharge in UAP patients(HR=2.023,95%CI:1.209-3.384).Conclusion In elderly UAP patients receiving drug treat-ment,a high TyG index is positively correlated with undergoing PCI after discharge,and the index is an independent risk factor for PCI in them.
6.Correlation between intrinsic capacity and triglyceride-glucose index in older adults from a Chinese community
Ruihan LIU ; Yutong LIU ; Xiang ZHOU ; Xiaomao WANG ; Jie ZHANG ; Fan TIAN ; Jian CAO
Chinese Journal of Geriatric Heart Brain and Vessel Diseases 2025;27(4):445-449
Objective To investigate the relationship of TyG index and IC.Methods A cross-sectional study was conducted with 1000 older adults living in Wanshou Road Community from May to December 2023.Finally 820 participants were enrolled,and based on the TyG index,they were divided into lower TyG index group(≤7.349,404 cases)and higher TyG index group(>7.349,416 cases).After PSM,there were only 522 participants subjected,including 261 individuals in the lower TyG index group 1 (≤7.349)and 416 ones in the higher TyG index group 2(>7.349).Univariate and multivariate logistic regression analyses were used to assess the correlation between IC and the TyG index as both continuous and categorical variables.PSM was employed to eliminate the confounding effects of covariates to identify the relationship between TyG index and IC in different categories.Results Before PSM,the neutrophil count,WBC count,and Hcy,FPG,TC,TG and HbA1c levels were significantly lower,and lymphocyte count,monocyte count,and AST level were obviously higher in the low TyG index group than the high TyG index group(P<0.05,P<0.01).After PSM,the low TyG index group still had notably lower FPG,TG and HbA1c than the high TyG index group(P<0.05,P<0.01).ROC curve analysis revealed that the cutoff value of TyG index was 7.349.Taking 7.349 as the cutoff value and TyG index as the cate-gorical variable,multivariate logistic regression analysis displayed that TyG index was correlated with IC[OR=3.921,95%CI:2.800-5.491,P=0.001(Model 1);OR=2.744,95%CI:1.739-4.329,P=0.001(Model 2);OR=2.744,95%CI:1.805-4.171,P=0.001(Model 3);OR=2.722,95%CI:1.530-4.843,P=0.001(after PSM)],indicating that TyG index remains an independent risk factor for IC.Conclusion IC is still correlated with TyG index in community-dwelling elderly individuals under different baseline conditions after adjusting for relevant laboratory indicators.As an indicator generated from routine blood test,TyG index has advantages in terms of cost and time.With further validation,TyG may provide a direction for studying IC prediction.
7.Correlation between intrinsic capacity and triglyceride-glucose index in older adults from a Chinese community
Ruihan LIU ; Yutong LIU ; Xiang ZHOU ; Xiaomao WANG ; Jie ZHANG ; Fan TIAN ; Jian CAO
Chinese Journal of Geriatric Heart Brain and Vessel Diseases 2025;27(4):445-449
Objective To investigate the relationship of TyG index and IC.Methods A cross-sectional study was conducted with 1000 older adults living in Wanshou Road Community from May to December 2023.Finally 820 participants were enrolled,and based on the TyG index,they were divided into lower TyG index group(≤7.349,404 cases)and higher TyG index group(>7.349,416 cases).After PSM,there were only 522 participants subjected,including 261 individuals in the lower TyG index group 1 (≤7.349)and 416 ones in the higher TyG index group 2(>7.349).Univariate and multivariate logistic regression analyses were used to assess the correlation between IC and the TyG index as both continuous and categorical variables.PSM was employed to eliminate the confounding effects of covariates to identify the relationship between TyG index and IC in different categories.Results Before PSM,the neutrophil count,WBC count,and Hcy,FPG,TC,TG and HbA1c levels were significantly lower,and lymphocyte count,monocyte count,and AST level were obviously higher in the low TyG index group than the high TyG index group(P<0.05,P<0.01).After PSM,the low TyG index group still had notably lower FPG,TG and HbA1c than the high TyG index group(P<0.05,P<0.01).ROC curve analysis revealed that the cutoff value of TyG index was 7.349.Taking 7.349 as the cutoff value and TyG index as the cate-gorical variable,multivariate logistic regression analysis displayed that TyG index was correlated with IC[OR=3.921,95%CI:2.800-5.491,P=0.001(Model 1);OR=2.744,95%CI:1.739-4.329,P=0.001(Model 2);OR=2.744,95%CI:1.805-4.171,P=0.001(Model 3);OR=2.722,95%CI:1.530-4.843,P=0.001(after PSM)],indicating that TyG index remains an independent risk factor for IC.Conclusion IC is still correlated with TyG index in community-dwelling elderly individuals under different baseline conditions after adjusting for relevant laboratory indicators.As an indicator generated from routine blood test,TyG index has advantages in terms of cost and time.With further validation,TyG may provide a direction for studying IC prediction.
8.Research progress on big-data-driven analysis strategies for imbalanced data of rare events
Jiangjie ZHOU ; Yutong WANG ; Tian FENG ; Xianglong MENG ; Baosheng LIANG ; Shengfeng WANG
Chinese Journal of Pharmacoepidemiology 2025;34(8):952-961
Rare events are widely prevalent in various disciplines,including rare adverse reactions to vaccines and drugs,clinical rare diseases,and low-probability clinical outcomes.The reason for research interest on such events is that their occurrence often brings incalculable and serious consequences.In the context of big data,numerous methods have emerged for rare event data analysis,including sampling based,category weighting,ensemble learning,and deep learning.This article systematically summarizes the research progress of current rare event data analysis methods,and introduces their basic principles and applicable scenarios.By analyzing the advantages and disadvantages of existing methods,the challenges of rare event research are sorted out and summarized,and potential research directions in related fields are explored to provide references for researchers.
9.Correlation between triglyceride glucose index and prognosis in elderly patients with unstable angina
Xiang ZHOU ; Ruihan LIU ; Yutong LIU ; Fan TIAN ; Jie ZHANG ; Xiaomao WANG ; Jian CAO
Chinese Journal of Geriatric Heart Brain and Vessel Diseases 2025;27(2):136-139
Objective To explore the correlation between triglyceride glucose(TyG)index and per-cutaneous coronary intervention(PCI)following drug treatment in elderly patients with unstable angina pectoris(UAP).Methods A total of 221 elderly UAP patients admitted to the Hyperbaric Oxygen Department of the First Medical Center of Chinese PLA General Hospital from March 2016 to March 2024 were enrolled,and based on the tertiles of the TyG index,they were divided into low,medium and high TyG index groups(the index:≤8.48,8.49-8.92,>8.92;with 74,74 and 73 cases,respectively).Clinical data of all patients were collected,and whether undergoing PCI after discharge was defined as the endpoint event.The follow-up ended on May 10,2024.The clini-cal data were compared in the three groups.Kaplan-Meier survival curves were plotted to compare the survival rates among the groups,and Cox proportional hazards regression model was em-ployed to analyze the influencing factors for occurrence of endpoint event.Results There were significant differences in the three groups in terms of TyG index,BMI,diabetes,FPG,TC,TG,LDL-C,HDL-C,HbA1c,NT-proBNP,and incidence of endpoint event(P<0.05,P<0.01).Univa-riate Cox proportional hazards regression analysis showed that the TyG index,diabetes,and HbA1c were risk factors for endpoint events in elderly patients with UAP(HR=2.523,95%CI:1.593-3.996;HR=2.543,95%CI:1.263-5.118;HR=1.434,95%CI:1.159-1.774).Further multivariate Cox proportional hazards regression analysis showed that,after adjusting for diabetes and HbA1c,the TyG index was an independent risk factor for PCI after discharge in UAP patients(HR=2.023,95%CI:1.209-3.384).Conclusion In elderly UAP patients receiving drug treat-ment,a high TyG index is positively correlated with undergoing PCI after discharge,and the index is an independent risk factor for PCI in them.
10.A nomogram model based on serological indicators for predicting in-hospital major adverse cardiovascular events in elderly patients with acute coronary syndrome
Xiang ZHOU ; Ruihan LIU ; Yutong LIU ; Fan TIAN ; Jie ZHANG ; Xiaomao WANG ; Jian CAO
Chinese Journal of Geriatrics 2025;44(3):289-296
Objective:To develop a nomogram model utilizing serological indicators for predicting in-hospital major adverse cardiovascular events(MACE)in elderly patients diagnosed with acute coronary syndrome(ACS).Methods:This study involved a retrospective analysis of clinical data from 1, 818 elderly patients with ACS who were treated at the First Medical Center of the General Hospital of the People's Liberation Army from January 2022 to May 2024.The patients were randomly assigned to a training set(1, 272 cases)and a validation set(546 cases)in a 7: 3 ratio.Following a comparison of the two groups, the training set was further categorized into non-MACE and MACE groups based on the occurrence of endpoint events.Univariate analysis, Lasso regression, and multivariate logistic regression analyses were sequentially employed to identify factors influencing in-hospital MACE and to construct the nomogram model.The performance of the model was assessed using receiver operating characteristic(ROC)curves, calibration curves, and decision curves.Results:Among the 1, 818 ACS patients, the mean age was 67 years(interquartile range: 61.0 to 73.0), with 70.4% being male.Almost all indicators(except platelet count)exhibited no statistically significant differences between the training and validation sets(all P>0.05).However, statistically significant differences(all P<0.05)were observed in age, body mass index, neutrophil count, lymphocyte count, monocyte count, white blood cell count, hemoglobin, red blood cell distribution width, mean platelet volume, C-reactive protein(CRP), fibrinogen, D-dimer, albumin, direct bilirubin, troponin T(TnT), fasting blood glucose(FBG), estimated glomerular filtration rate(eGFR), uric acid, N-terminal pro-B-type natriuretic peptide(NT-proBNP), glycated hemoglobin(HbA1c), and high-density lipoprotein cholesterol(HDL-C)between the non-MACE and MACE groups in the training set.Ultimately, seven variables—neutrophil count, hemoglobin, red blood cell distribution width, CRP, TnT, FBG, and NT-proBNP—were selected to construct the nomogram model.The model demonstrated high discrimination in both the training and validation sets, with an area under the curve of 0.86(95% CI: 0.82-0.90)for the training set and 0.85(95% CI: 0.81-0.90)for the validation set.Furthermore, the calibration curves for both cohorts indicated a close agreement between predicted and actual risk estimates, suggesting improved model calibration.Decision curve analysis indicated that the predictive model has notable clinical utility. Conclusions:The constructed nomogram enhances the accuracy of predicting in-hospital MACE in elderly patients with ACS, thereby offering a valuable reference for clinical practice.

Result Analysis
Print
Save
E-mail