1.Visualization analysis of literature on the effect of lipid metabolism on osteoporosis
Jie HUANG ; Hao ZENG ; Wenchi WANG ; Zhucheng LYU ; Wei CUI
Chinese Journal of Tissue Engineering Research 2026;30(6):1558-1568
BACKGROUND:Studies have shown that lipid metabolism and related diseases can affect the development of osteoporosis.OBJECTIVE:Using bibliometric visualization analysis software to analyze and summarize the frontier content and research hotspots in the field of lipid metabolism affecting osteoporosis.METHODS:Using the Web of Science core collection database as the retrieval platform,relevant literature regarding the effect of lipid metabolism on osteoporosis from 2004 to 2024 was retrieved.VOSviewer and CiteSpace were used for bibliometric and visual analyses.RESULTS AND CONCLUSION:A total of 1 277 articles were included,and the number of articles on the effect of lipid metabolism on osteoporosis at home and abroad was increasing year by year.The number of articles published in China was 417,ranking first,and the United States was 243,ranking second.Shanghai Jiao Tong University ranked first with 30 articles.Professor Rosen Clifford J from Tufts University School of Medicine and Professor Recker Robert R from Clayton University were the most cited authors.The number of documents published in BONE in the Netherlands ranked first,and the JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM in England was the most cited journal.Bone mineral density,bone metabolism,menopause,and obesity were the core keywords,and they were also research hotspots in this field.The above results show that in the past 20 years,research in the field of lipid metabolism affecting osteoporosis has focused on the role of abnormal lipid metabolism in bone mineral density and bone metabolism,thereby regulating osteoporosis and post-menopause osteoporosis.Clarifying the pathway of this mechanism and"bone-lipid balance"is the future research idea and direction.
2.Visualization analysis of literature on the effect of lipid metabolism on osteoporosis
Jie HUANG ; Hao ZENG ; Wenchi WANG ; Zhucheng LYU ; Wei CUI
Chinese Journal of Tissue Engineering Research 2026;30(6):1558-1568
BACKGROUND:Studies have shown that lipid metabolism and related diseases can affect the development of osteoporosis.OBJECTIVE:Using bibliometric visualization analysis software to analyze and summarize the frontier content and research hotspots in the field of lipid metabolism affecting osteoporosis.METHODS:Using the Web of Science core collection database as the retrieval platform,relevant literature regarding the effect of lipid metabolism on osteoporosis from 2004 to 2024 was retrieved.VOSviewer and CiteSpace were used for bibliometric and visual analyses.RESULTS AND CONCLUSION:A total of 1 277 articles were included,and the number of articles on the effect of lipid metabolism on osteoporosis at home and abroad was increasing year by year.The number of articles published in China was 417,ranking first,and the United States was 243,ranking second.Shanghai Jiao Tong University ranked first with 30 articles.Professor Rosen Clifford J from Tufts University School of Medicine and Professor Recker Robert R from Clayton University were the most cited authors.The number of documents published in BONE in the Netherlands ranked first,and the JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM in England was the most cited journal.Bone mineral density,bone metabolism,menopause,and obesity were the core keywords,and they were also research hotspots in this field.The above results show that in the past 20 years,research in the field of lipid metabolism affecting osteoporosis has focused on the role of abnormal lipid metabolism in bone mineral density and bone metabolism,thereby regulating osteoporosis and post-menopause osteoporosis.Clarifying the pathway of this mechanism and"bone-lipid balance"is the future research idea and direction.
3.Research progress on oral microecological imbalance and intervention strategies after radiotherapy for head and neck tumors
LIU Xue ; LI Yufei ; YANG Xinyao ; LI Hao ; ZHANG Ailin ; CUI Lei ; HUANG Zhengwei ; HOU Lili
Journal of Prevention and Treatment for Stomatological Diseases 2026;34(4):385-394
Radiotherapy is a crucial treatment modality for head and neck tumors. However, while effectively killing tumor cells, it significantly disrupts the homeostasis of the oral microecology, which is closely associated with various complications such as radiation-induced oral mucositis. Literature review indicates that as radiotherapy doses accumulate and treatment durations extend, the richness and diversity of the oral microbiota show a declining trend, with the genus Streptococcus decreasing most markedly. In contrast, radiotherapy selectively promotes the proliferation of bacterial phyla such as Proteobacteria and Bacteroidetes, which are rich in opportunistic pathogens. Mechanistically, radiotherapy activates the nuclear factor-kappa B pathway, triggering chronic inflammation and oxidative stress, damaging the epithelial barrier, suppressing local immunity, and causing damage to organs such as the salivary glands. It can also induce systemic diseases via the oral-gut axis, forming a multi-level, interconnected pathogenic network. In terms of interventions, treatment strategies including probiotics and prebiotics have shown promising efficacy against side effects such as radiation-induced oral mucositis. Saliva-based oral microbiota transplantation is an emerging strategy that is expected to become widely utilized for restoring oral microecological balance. Existing interventions provide preliminary pathways for clinical practice, but this field still faces several key scientific questions. The association between oral microecology and systemic diseases remains largely correlative, lacking causal evidence. Furthermore, critical parameters for oral microbiota transplantation, such as donor screening criteria, transplantation protocols, and long-term safety, are not yet well-defined. Therefore, future research should focus on conducting large-scale clinical trials to establish standardized protocols and safety evaluation systems for oral microecological interventions, and explore combined treatment therapies such as probiotics, prebiotics, and microbiota transplantation to advance the development of personalized precision modulation. These will enable more effective management of radiotherapy-induced oral microecological dysbiosis and improve treatment outcomes and quality of life for patients with head and neck tumors.
4.Effect of Yigan Fupi Prescription (抑肝扶脾方) on the AKT/mTOR Pathway in the Colon Tissue of Diarrhea-Type Irritable Bowel Syndrome Model Rats with Liver Stagnation and Spleen Deficiency Pattern
Suting JIU ; Huiying LI ; Yueting SUN ; Songxiang CUI ; Xintian XU ; Hao ZHENG ; Weimin LU
Journal of Traditional Chinese Medicine 2025;66(3):290-299
ObjectiveTo explore the possible mechanism of Yigan Fupi Prescription (抑肝扶脾方, YFP) in treating diarrhea-type irritable bowel syndrome (IBS-D) by investigating the AKT/mTOR signaling pathway. MethodsSixty SD rats were randomly divided into control group, model group, YFP low-, medium-, and high-dose group, and pinaverium bromide group, with 10 rats in each group. All groups but the control group, were subjected to 21 days of tail-clamping stimulation and 14 days of senna leaf gavage to establish a liver stagnation and spleen deficiency-type IBS-D rat model. After successful modeling, the YFP low-, medium-, and high-dose group were administered 0.96, 1.93, and 3.87 g/(kg·d) of the prescription, respectively. The pinaverium bromide group was given 13.5 mg/(kg·d), while the control and model groups were given 10 ml/(kg·d) distilled water. All groups were administered once daily for 14 consecutive days. General conditions of the rats were recorded during the experiment, and after modeling and drug administration, body weight, Bristol stool score, abdominal withdrawal reflex (AWR) score, and histo pathology of colon tissue were observed under HE staining. ELISA was used to detect serum levels of tumor necrosis factor α (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6). Immunofluorescence was employed to detect the levels of AKT/mTOR pathway-related proteins including phosphorylated AKT (p-AKT)/AKT and phosphorylated mTOR (p-mTOR)/mTOR in the colon tissue. Western Blotting was used to detect the levels of autophagy-related proteins, including UNC-51-like kinase 1 (ULK1), Beclin1 and LC3, and tight junction proteins including Occludin and ZO-1 in the colon tissue. ResultsAfter modeling, compared to the control group, the body weight of rats in the other groups decreased, and Bristol stool scores, as well as AWR scores under 20, 40, 60, and 80 mmHg increased (P<0.05 or P<0.01). After drug administration, compared to the control group, the model group showed reduced body weight, decreased ULK1, Beclin1, LC3Ⅱ/LC3Ⅰ, Occludin, and ZO-1 protein levels in the colon tissue (P<0.05 or P<0.01), and increased Bristol stool scores, AWR scores, serum TNF-α, IL-1β, and IL-6 levels, as well as p-AKT/AKT and p-mTOR/mTOR protein relative expression levels (P<0.05 or P<0.01). Pathological results showed a significant reduction in goblet cells in the upper part of the glandular layer of the colon, with mild inflammatory cell infiltration. The submucosal collagen fibers were dissolved, with unclear boundaries, pale staining, and microvascular congestion and dilation. Compared with the model group, the YFP low-, medium-, and high-dose group and the pinaverium bromide group showed increased body weight, Beclin1, Occludin, and LC3Ⅱ/LC3Ⅰ protein levels (P<0.05 or P<0.01), and decreased Bristol stool scores, AWR scores under 40, 60, and 80 mmHg, serum IL-1β, IL-6, TNF-α levels, and p-AKT/AKT, p-mTOR/mTOR protein relative expression levels (P<0.05 or P<0.01). The pathological morphology of the rats in the YFP groups and pinaverium bromide group showed varying degrees of improvement. Compared with the pinaverium bromide group, the YFP low- and medium-dose group showed increased AWR scores under 20, 40, and 60 mmHg (P<0.05). The YFP low-dose group had reduced TNF-α, IL-1β, and IL-6 levels, and increased p-mTOR/mTOR protein relative expression levels occured in all YFP groups (P<0.05). Compared with the YFP low-dose group, the YFP high-dose group and pinaverium bromide group showed decreased AWR scores under different pressure levels and reduced p-AKT/AKT protein relative expression levels, while the YFP medium- and high-dose group had elevated serum TNF-α, IL-1β levels and reduced p-mTOR/mTOR protein relative expression levels (P<0.05). ConclusionYFP can effectively improve the pathological injury of colon tissue in IBS-D model rats with liver stagnation and spleen deficiency, reduce Bristol stool and AWR scores, and its mechanism may be related to reducing level of inflammatory factors and inhibiting AKT/mTOR pathway-related proteins in colon tissue, thereby enhancing the expression of autophagy-related proteins in the colon tissue.
5.The value of coronary CT angiography-based traditional features and radiomics in identification of culprit plaques to cause acute myocardial infarction
Pei NIE ; Shuo ZHANG ; Yan DENG ; Shifeng YANG ; Xinxin YU ; Kaiyue ZHI ; He ZHU ; Peng LI ; Jingjing CUI ; Wenjing CHEN ; Yanmei WANG ; Yuchao XU ; Dapeng HAO ; Ximing WANG
Chinese Journal of Radiology 2025;59(9):1017-1028
Objective:To investigate the value of coronary CTA (CCTA)-based traditional features and radiomics of plaque in the identification of culprit lesions that caused acute myocardial infarction (AMI).Methods:This was a retrospective multicenter study. From July 2016 to November 2023, a total of 344 patients from the Affiliated Hospital of Qingdao University (training cohort, n=184), Shandong Provincial Hospital Affiliated to Shandong First Medical University (validation cohort, n=88) and Qilu Hospital of Shandong University (test cohort, n=72) who received percutaneous coronary intervention (PCI) due to AMI and underwent CCTA within 48 hours of AMI were enrolled. The culprit plaques and non-culprit plaques were identified using a combination of electrocardiogram, CCTA, and angiographic findings. The vessel, plaque location, plaque type, Coronary Artery Disease-Reporting and Data System (CAD-RADS) score, high-risk plaque characteristics, plaque length, plaque volume, and burden were analyzed, and 1 904 radiomics features were extracted for each plaque. The traditional imaging model, the radiomics model, and the combined model were established by using multivariate Logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each model in identifying culprit lesions. The DeLong test was used for the comparison of AUC between every two models. The net reclassification index (NRI) was used to evaluate the incremental value of the combined model to the traditional imaging model and the radiomics model. The decision curve analysis (DCA) was used to assess the clinical net benefit of these models. A correlation heatmap was used to evaluate the correlation between the radiomics score and traditional CCTA factors. The interpretable analysis of the decision process of the combined model was performed by the Shapley Additive exPlanations (SHAP). Results:In the validation cohort and the test cohort, the AUC of the traditional imaging model developed by the vessel, plaque type, positive remodeling and CAD-RADS score was 0.898 (95% CI 0.869-0.922) and 0.881 (95% CI 0.848-0.910), respectively. The radiomics model developed by six radiomics features was 0.863 (95% CI 0.831-0.891) and 0.863 (95% CI 0.827-0.864), respectively. The AUC of the combined model was 0.930 (95% CI 0.905-0.950)and 0.919 (95% CI 0.889-0.942), respectively. In the validation cohort and the test cohort, the AUC of the combined model was higher than that of the traditional imaging model ( Z=4.013, 4.272, P<0.001) and that of the radiomics model ( Z=4.819, 3.784, P<0.001), respectively. In the validation cohort, the combined model yielded an NRI of 20.43% (95% CI 10.43%-30.44%, P<0.001) and 20.21% (95% CI 9.62%-30.80%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. In the test cohort, the combined model yielded an NRI of 28.05% (95% CI 16.72%-39.38%, P<0.001) and 23.57% (95% CI 13.58%-33.56%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. DCA showed the combined model had the highest clinical net benefit. The correlation heatmap showed the radiomics score was not correlated or only weakly correlated with traditional CCTA factors. SHAP indicated the radiomics and CAD-RADS score contributed significantly to the model. Conclusion:The CCTA-based traditional features and radiomics of plaque have favorable performance for the identification of culprit plaques in patients with AMI.
6.Nomogram model based on enhanced MRI radiomics,deep learning and clinical features for differentiating spinal tuberculosis and pyogenic spondylitis
Xirui LI ; Dezhi WANG ; Xiaonan YANG ; Jie LI ; Dapeng HAO ; Jiufa CUI
Chinese Journal of Medical Imaging Technology 2025;41(1):122-127
Objective To observe the efficacy of nomogram model based on enhanced MRI radiomics,deep learning(DL)and clinical features for differentiating spinal tuberculosis and pyogenic spondylitis.Methods Totally 59 cases of spinal tuberculosis and 66 of pyogenic spondylitis were retrospectively enrolled.Radiomics,DL and clinical features relevant to differentiating spinal tuberculosis and pyogenic spondylitis were selected.Then a predictive model was constructed using logistic regression based on the selected optimal features,and a comprehensive nomogram model was developed through combination of the above features.The effectiveness of these models for distinguishing spinal tuberculosis from pyogenic spondylitis were visualized based on receiver operating characteristic curves,calidration curves and decision curves.Results The nomogram model demonstrated the highest area under the curve(AUC)in both training set and test set,with AUC of 0.997 and 0.920,respectively.In test set,DeLong test indicated that the difference of AUC between the nomogram model and clinical model was significant(P=0.002),while no significant difference was observed between the nomogram model and the other models(all P>0.05).The nomogram model provided the highest overall net benefit and exhibited good calibration for distinguishing spinal tuberculosis from pyogenic spondylitis.Conclusion Nomogram model based on enhanced MRI radiomics,DL and clinical features demonstrated high efficacy for differentiating spinal tuberculosis from pyogenic spondylitis.
7.Association between estimated cumulative LDL-C exposure and coronary artery disease severity and 2-year prognosis in acute coronary syndrome patients
Yichun HAO ; Jing CHEN ; Shaodi YAN ; Ying SONG ; Lin JIANG ; Yan CHEN ; Cheng CUI ; Zhan GAO ; Xueyan ZHAO ; Yin ZHANG ; Lijian GAO ; Jue CHEN ; Jinqing YUAN ; Lei SONG ; Jingjing XU
Chinese Journal of Cardiology 2025;53(3):274-280
Objective:To investigate the association between estimated cumulative low-density lipoprotein cholesterol (LDL-C) exposure and the severity of coronary artery disease and long-term adverse cardiovascular and cerebrovascular events (MACCE) in patients with acute coronary syndrome (ACS).Methods:The subjects were from the PROMISE study. This study was a prospective cohort study led by Fuwai Hospital, Chinese Academy of Medical Sciences, with participation from eight regional tertiary hospitals as sub-centers, and enrolled 18 701 patients with confirmed coronary heart disease between January 2015 and May 2019. Among them, 8 429 patients with ACS were included in this study. The estimated cumulative LDL-C exposure was calculated by multiplying LDL-C by age. Participants were then divided into four groups based on quartiles. Baseline data and coronary angiography data were collected, and participants were followed for 2 years. The primary endpoint was MACCE, which was composed of all-cause death, cardiac death, myocardial infarction, revascularization, and stroke. Spearman correlation analysis was used to estimate the correlation between cumulative LDL-C exposure and the severity of coronary artery disease. The differences in MACCE among the four groups were compared, and multivariate Cox regression was used to divide the estimated cumulative exposure LDL-C into two groups, three groups, and four groups to analyze its relationship with MACCE.Results:The 8 429 ACS patients included in the study had an age of (60.9±11.4) years, with 1 951(23.1%) females. Spearman correlation analysis revealed that estimated cumulative LDL-C exposure was positively associated with the preoperative SYNTAX score, three-vessel lesions disease, left main disease, and the number of target lesions (correlation coefficients r=0.14, 0.10, 0.04 and 0.03, respectively, with all P<0.05). The 2-year follow-up results indicated that the incidence rates of MACCE, all-cause death, cardiac death, myocardial infarction, and stroke in ACS patients grouped by different levels of estimated cumulative LDL-C exposure were statistically significant (all P<0.05). The results of the Cox multivariate regression analysis showed that when the estimated cumulative LDL-C exposure was treated as a continuous variable and analyzed in two, three, and four groups, with the lowest group as the reference, the risk of MACCE occurrence in the high-value group increased by 21% (95% CI 1.08-1.37, P=0.002), 24% (95% CI 1.07-1.43, P=0.004), and 21% (95% CI 1.02-1.43, P=0.025) respectively. Conclusions:A positive correlation was found between estimated cumulative LDL-C exposure and severity of coronary artery disease. High estimated cumulative LDL-C exposure level is a risk factor for MACCE in ACS patients within 2 years.
8.The correlation of serum hypoxia-inducible factor-1α level with cerebral microbleeds and cognitive impairment
Qing LI ; Xiaowen ZHAO ; Jing REN ; Miao YU ; Hanfang CUI ; Fangyuan DING ; Hao LIU ; Qiong LI ; Fan WANG ; Qing LI ; Xiyan CHEN ; Chengbiao LU ; Shaomin LI ; Jianhua ZHAO
Journal of Capital Medical University 2025;46(2):216-227
Objective To explore the correlation between serum hypoxia-inducible factor-1α(HIF-1α)levels and cerebral microbleeds(CMBs)and cognitive impairment and to assess the predictive value of HIF-1α for CSVD-related cognitive impairment.Methods A total of 104 patients with CSVD who attended the Department of Neurology,First Affiliated Hospital of Xinxiang Medical University from June 2022 to November 2023 were enrolled.All enrolled patients were subjected to basic statistics,cranial nuclear magnetic resonance examination,cognitive function assessment,and serum HIF-1α test,and the number and location of CMBs were counted.Based on the above data the enrolled patients were grouped.The correlation between HIF-1α and cognitive function and CMBs was studied the influencing factors of CMBs and cognitive impairment were analyzed,and the predictive value of HIF-1α on the occurrence of cognitive impairment was evaluated.Results There were statistically significant differences in HIF-1α levels and cognitive function among different CMBs groups.Serum HIF-1α levels were significantly negatively correlated with overall cognitive function,visuospatial and executive function,attention,and delayed recall,and serum HIF-1α was positively correlated with the number of CMBs.HIF-1α may be a risk factor for CMBs and cognitive impairment associated with CSVD,and serum HIF-1α has potential in predict the cognitive impairment caused by CSVD.Conclusion Serum levels of HIF-1α were associated with the number of CMB and CSVD-related cognitive impairment,and serum levels of HIF-1α may have a predictive value for CSVD-related cognitive impairment.
9.Whole genome sequencing and analysis of multidrug resistant ST314 Salmonella Kentucky from a broiler slaughterhouse
Jia-rui LI ; Rui-yuan SUN ; Pei-jie HE ; Hao-tian LIU ; Ru-yi KUANG ; Jing XIA ; Min CUI ; Yong HUANG ; Li-kou ZOU ; Xin-feng HAN
Chinese Journal of Zoonoses 2025;41(5):537-543
This study investigated the potential pathogenicity and genetic characteristics of ST314 Salmonella Kentucky(S.Ken-tucky)isolates from a broiler slaughterhouse.Antimicrobial susceptibility testing and whole-genome sequencing(WGS)were used to determine antimicrobial resistance,virulence factors,and the presence of antimicrobial resistance genes(ARGs)and mobile genetic elements(MGEs)among the isolates.The three multidrug resistant(MDR)isolates exhibited high resistance to multiple antimicrobial agents.The F4-2S strain exhibited resistance to 14 drugs across seven categories,whereas the F4T strain showed resistance to 13 drugs in the same number of categories.In contrast,the Y23 strain was resistant to nine drugs in six categories.Notably,F4-2S dem-onstrated high homology with F4T:both possessed 13 ARGs distributed across nine categories,in addition to a wide range of virulence factors,including secretion systems and effector proteins.The presence of IncR and IncX1 plasmids significantly enhanced both the antimicrobial resistance and pathogenicity of the isolates.The genome map of Y23 revealed a chromosome alongside two plasmids.The chromosome containedonly one resistance gene but several virulence factors,including the type III secretion system(T3SS),which is crucial for bacterial invasion.The plasmid pY23-1 contained eight types of 19 ARGs.Comparative analysis indicated that pY23-1 ex-hibited high homology with pZ1323SSL0055 and pSAL-045,all of which contained multiple ARGs,thus suggesting critical roles of these genes in the evolution of bacterial resistance.In conclusion,ST314 S.Kentucky demonstrated a complex mechanism of resis-tance coupled with significant pathogenic potential.The ARGs and MGEs in the plasmid contributed to the emergence and dissemina-tion of antimicrobial resistance.The multiple virulence factors present in the chromosome may be key factors driving the increasing virulence of ST314 S.Kentucky.
10.Comparison of random forest and Cox regression models for predicting long-term survival after radical resection of HBV-associated hepatocellu-lar carcinoma
Guang-zhou LI ; Hong-lei WANG ; Xi-quan CHEN ; Yang HE ; Yan-hao CHEN ; Cui HU ; Miao WANG ; De-xiao ZHANG
Chinese Journal of Current Advances in General Surgery 2025;28(5):355-360
Objective:To analyze the factors associated with long-term survival after radical resection of hepatitis B virus(HBV)-associated hepatocellular carcinoma(HCC),and to construct random forest and Cox regression models,to evaluate the two models.Methods:A total of 368 patients with HBV-infected HCC who underwent radical resection were selected retrospectively.These patients were categorized as having a good prognosis(n=266)or a poor prognosis(n=102)based on their survival and mortality status.Univariate and Cox regression analysis were used to identify fac-tors that predict poor prognosis in HCC patients after surgery,and Cox regression and random forest prediction models were constructed and evaluated.Results:There were significant differences in smoking history,Child-Pugh classifica-tion,cirrhosis,microvascular invasion,TNM staging,tumor capsule integrity,platelet-to-lymphocyte ratio(PLR),regular antiviral therapy,HBV-DNA load,alpha-fetoprotein(AFP),neutrophil-to-lymphocyte ratio(NLR),systemic immune in-flammatory index(SII),and albumin-to-globulin ratio(AGR)between the two groups(P<0.05);Cox regression showed that cirrhosis,microvascular invasion,regular antiviral treatment,HBV-DNA load,NLR,PLR,SII,and AGR were related factors that negatively affected the prognosis of patients with HBV-infected HCC after surgery(P<0.05),with an AUC of 0.870 for predicting prognosis;the importance ranking obtained by the random forest model was HBV-DNA load,cirrho-sis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII,with an AUC of 0.926 for predicting prog-nosis;the AUC predicted by the random forest model was greater than that predicted by the Cox regression model(Z=2.411,P=0.016).Conclusion:HBV-DNA load,cirrhosis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII are factors that affect the poor prognosis of patients with HBV-related HCC after surgery.The random for-est prediction model constructed based on these factors has high predictive value and is superior to the Cox regression prediction model.


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