1.Brucea javanica Seed Oil Emulsion and Shengmai Injections Improve Peripheral Microcirculation in Treatment of Gastric Cancer.
Li QUAN ; Wen-Hao NIU ; Fu-Peng YANG ; Yan-da ZHANG ; Ru DING ; Zhi-Qing HE ; Zhan-Hui WANG ; Chang-Zhen REN ; Chun LIANG
Chinese journal of integrative medicine 2025;31(4):299-310
OBJECTIVE:
To explore and verify the effect and potential mechanism of Brucea javanica Seed Oil Emulsion Injection (YDZI) and Shengmai Injection (SMI) on peripheral microcirculation dysfunction in treatment of gastric cancer (GC).
METHODS:
The potential mechanisms of YDZI and SMI were explored through network pharmacology and verified by cellular and clinical experiments. Human microvascular endothelial cells (HMECs) were cultured for quantitative real-time polymerase chain reaction, Western blot analysis, and human umbilical vein endothelial cells (HUVECs) were cultured for tube formation assay. Twenty healthy volunteers and 97 patients with GC were enrolled. Patients were divided into surgical resection, surgical resection with chemotherapy, and surgical resection with chemotherapy combining YDZI and SMI groups. Forearm skin blood perfusion was measured and recorded by laser speckle contrast imaging coupled with post-occlusive reactive hyperemia. Cutaneous vascular conductance and microvascular reactivity parameters were calculated and compared across the groups.
RESULTS:
After network pharmacology analysis, 4 ingredients, 82 active compounds, and 92 related genes in YDZI and SMI were screened out. β-Sitosterol, an active ingredient and intersection compound of YDZI and SMI, upregulated the expression of vascular endothelial growth factor A (VEGFA) and prostaglandin-endoperoxide synthase 2 (PTGS2, P<0.01), downregulated the expression of caspase 9 (CASP9) and estrogen receptor 1 (ESR1, P<0.01) in HMECs under oxaliplatin stimulation, and promoted tube formation through VEGFA. Chemotherapy significantly impaired the microvascular reactivity in GC patients, whereas YDZI and SMI ameliorated this injury (P<0.05 or P<0.01).
CONCLUSIONS
YDZI and SMI ameliorated peripheral microvascular reactivity in GC patients. β-Sitosterol may improve peripheral microcirculation by regulating VEGFA, PTGS2, ESR1, and CASP9.
Humans
;
Microcirculation/drug effects*
;
Drugs, Chinese Herbal/administration & dosage*
;
Stomach Neoplasms/physiopathology*
;
Emulsions
;
Male
;
Plant Oils/administration & dosage*
;
Brucea/chemistry*
;
Middle Aged
;
Female
;
Drug Combinations
;
Human Umbilical Vein Endothelial Cells/metabolism*
;
Seeds/chemistry*
;
Injections
;
Vascular Endothelial Growth Factor A/metabolism*
;
Aged
;
Network Pharmacology
2.NFKBIE: Novel Biomarkers for Diagnosis, Prognosis, and Immunity in Colorectal Cancer: Insights from Pan-cancer Analysis.
Chen Yang HOU ; Peng WANG ; Feng Xu YAN ; Yan Yan BO ; Zhen Peng ZHU ; Xi Ran WANG ; Shan LIU ; Dan Dan XU ; Jia Jia XIAO ; Jun XUE ; Fei GUO ; Qing Xue MENG ; Ren Sen RAN ; Wei Zheng LIANG
Biomedical and Environmental Sciences 2025;38(10):1320-1325
3.Progress in the Application of Stellate Ganglion Block in Non-Analgesic Fields.
Peng-Cheng YE ; Ying REN ; Wen-Liang SU ; Hao KONG
Acta Academiae Medicinae Sinicae 2025;47(3):462-469
Stellate ganglion block (SGB) is a specific type of peripheral nerve block in which local anesthetics and/or steroids are injected around the stellate ganglia.In the past,SGB was mainly used to alleviate pain-related syndromes.With the development of ultrasound technology,SGB has been widely used in non-analgesic fields,demonstrating significant therapeutic effects on arrhythmias,hot flashes,psychiatric disorders,cerebrovascular diseases,insomnia,and post coronavirus disease-2019 conditions in recent years.This study reviews the progress in the application of SGB in the non-analgesic fields.
Stellate Ganglion
;
Humans
;
Autonomic Nerve Block/methods*
;
Anesthetics, Local/administration & dosage*
;
COVID-19
4.Cinnamaldehyde inhibits growth, metastasis and induces apoptosis of human endometriotic cells through RPS7
Xiaoxuan Zhan ; Chengyi Liu ; Jiahua Peng ; Shuzhen Liu ; Xin Li ; Yunying Ren ; Danni Chen ; Peishuang Li ; Ruining Liang
Acta Universitatis Medicinalis Anhui 2025;60(3):405-413
Objective :
To investigate the effects of cinnamaldehyde(CA) on the growth, metastasis and apoptosis of human endometriosis(EMs) cells and to explore whether the mechanism is related to ribosomal protein S7(RPS7) expression.
Methods :
Endometriosis cells were divided into control group, CA group, sh-NC group, CA+sh-RPS7 group. Effects of CA on cell growth in human endometriotic cells were determined using Cell Counting Kit-8(CCK-8) and colony formation assay. Effects of CA on cell metastasis were performed by motility assay and Transwell assay. Effects of CA on cell apoptosis were evaluated by Hoechst 33258 staining and flow cytometry. Meanwhile, the levels of PCNA, E-cadherin, Vimentin, Bax and Bcl-2 were evaluated using Western blot in human endometriotic cells with treatment CA. The expression of RPS7 was detected by qRT-PCR and Western blot assay. The RPS7 overexpression of human endometriotic cells was established by cell transfection. CA-mediated effects on cell proliferation and apoptosis were determined by CCK-8 assay and flow cytometry in human endometriotic cells with RPS7 overexpression.
Results :
CA repressed cell growth as well as down-regulated PCNA. The half inhibitory concentration(IC50) value was 53.60 μmol/L after 24 h treatment, and colony formation rate was 25.32%. Additionally, CA inhibited metastasis which was associated with downregulated Vimentin and upregulated E-cadherin. The relative migration rates were 35% and 29% as well as invasion rate was 40%. Further, CA induced apoptosis by cell cycle G2/M phase arrest and cell apoptosis rate was 25.1%, which related to the up-regulation of of Bax and the down-regulation of Bcl-2. CA inhibited the expression of RPS7 and overexpression of RPS7 promoted cell proliferation and suppressed apoptosis in CA-mediated cells.
Conclusion
CA inhibits cell growth, metastasis, and induces cell apoptosis by downregulating the expression of RPS7.
5.Pregnancy probability prediction models based on 5 machine learning algorithms and comparison of their performance
Chao REN ; Huan YANG ; Niya ZHOU ; Qing CHEN ; Wenzheng ZHOU ; Tong WANG ; Xi LING ; Lei SUN ; Peng ZOU ; Zhuoyue LIANG ; Lin AO ; Jinyi LIU ; Jia CAO
Journal of Army Medical University 2025;47(12):1376-1387
Objective To construct 5 machine-learning models and compare their performance in predicting the associations between pre-pregnancy socio-psycho-behavioral exposures of both spouses and preconception outcomes.Methods Based on Chongqing Preconception Reproductive Health and Birth Outcome Cohort of volunteers recruited from Chongqing Health Center for Women and Children during January 2019 and March 2022,5 447 couples were recruited and surveyed through interviewer-interview for the demographic and social-psychological-behavioral data of both spouses(221 variables).According to the inclusion and exclusion criteria,4 097 couples were finally included,and randomly assigned into a training set(n=2 867 spouses)and a validation set(n=1 230 spouses)at a ratio of 7∶3.Feature analysis and collinear screening were applied to select the potential exposure factors.In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions,feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set.Five algorithms,that is,Logistic Regression,Naive Bayes,Random Forest,Gradient Boosting Machine,and Support Vector Machine,were used to construct preconception outcome prediction models,and the parameters of each model were optimized using random search combined with grid search.The predictive performance of each model was compared using precision,recall,F1 score,area under the receiver operating characteristic curve(AUC),and calibration curve.The optimal model was then selected by comparing the changes in the predictive ability of the questionnaire data for fertility outcomes with or without semen parameters.Results There were 24 variables screened out in feature Set 1,and 16 variables in feature Set 2.In feature Set 1,the gradient boosting machine performed better,with a relatively higher AUC value(0.651)and better F1 score(0.61).The logistic regression model performed stably(AUC value=0.647)and was suitable as the reference model.The random forest(AUC value=0.641),Naive Bayes(AUC value=0.641),and support vector machine(AUC value=0.634)performed second-best.By utilizing the gradient boosting machine,comparable results were found between the predictions from feature sets with or without semen parameters,as in feature Set 1,the AUC value of its validation set was 0.651(95%CI:0.629~0.681),the prediction accuracy was 0.63,the recall rate was 0.65,and the average precision value F1 was 0.61;and in feature Set 2,the AUC value of its validation set was 0.649(95%CI:0.624~0.663),and both the calibration curves were close to the ideal curve.The prediction results indicated that in feature Set 1,the features highly negatively correlated with preconception outcomes were female age,male age,and no pregnancy within 1 year without contraception,while the features highly positively correlated with preconception outcomes were female pregnancy history,total sperm vitality,and use of contraceptive measures before enrollment.Conclusion Among the 5 machine-learning algorithms performed in this cohort data,the gradient boosting machine shows slightly better performance.There are 24 factors being associated with preconception outcomes in both spouses,and the performance of the simplified model excluding semen parameters is not significantly declined.It is feasible to use machine-learning methods to predict human preconception outcomes through social-psychological-behavioral questionnaires.
6.Omics for deciphering oral microecology
Lin YONGWANG ; Liang XIAOYUE ; Li ZHENGYI ; Gong TAO ; Ren BIAO ; Li YUQING ; Peng XIAN
International Journal of Oral Science 2024;16(2):197-207
The human oral microbiome harbors one of the most diverse microbial communities in the human body,playing critical roles in oral and systemic health.Recent technological innovations are propelling the characterization and manipulation of oral microbiota.High-throughput sequencing enables comprehensive taxonomic and functional profiling of oral microbiomes.New long-read platforms improve genome assembly from complex samples.Single-cell genomics provides insights into uncultured taxa.Advanced imaging modalities including fluorescence,mass spectrometry,and Raman spectroscopy have enabled the visualization of the spatial organization and interactions of oral microbes with increasing resolution.Fluorescence techniques link phylogenetic identity with localization.Mass spectrometry imaging reveals metabolic niches and activities while Raman spectroscopy generates rapid biomolecular fingerprints for classification.Culturomics facilitates the isolation and cultivation of novel fastidious oral taxa using high-throughput approaches.Ongoing integration of these technologies holds the promise of transforming our understanding of oral microbiome assembly,gene expression,metabolites,microenvironments,virulence mechanisms,and microbe-host interfaces in the context of health and disease.However,significant knowledge gaps persist regarding community origins,developmental trajectories,homeostasis versus dysbiosis triggers,functional biomarkers,and strategies to deliberately reshape the oral microbiome for therapeutic benefit.The convergence of sequencing,imaging,cultureomics,synthetic systems,and biomimetic models will provide unprecedented insights into the oral microbiome and offer opportunities to predict,prevent,diagnose,and treat associated oral diseases.
7.Omics for deciphering oral microecology
Lin YONGWANG ; Liang XIAOYUE ; Li ZHENGYI ; Gong TAO ; Ren BIAO ; Li YUQING ; Peng XIAN
International Journal of Oral Science 2024;16(2):197-207
The human oral microbiome harbors one of the most diverse microbial communities in the human body,playing critical roles in oral and systemic health.Recent technological innovations are propelling the characterization and manipulation of oral microbiota.High-throughput sequencing enables comprehensive taxonomic and functional profiling of oral microbiomes.New long-read platforms improve genome assembly from complex samples.Single-cell genomics provides insights into uncultured taxa.Advanced imaging modalities including fluorescence,mass spectrometry,and Raman spectroscopy have enabled the visualization of the spatial organization and interactions of oral microbes with increasing resolution.Fluorescence techniques link phylogenetic identity with localization.Mass spectrometry imaging reveals metabolic niches and activities while Raman spectroscopy generates rapid biomolecular fingerprints for classification.Culturomics facilitates the isolation and cultivation of novel fastidious oral taxa using high-throughput approaches.Ongoing integration of these technologies holds the promise of transforming our understanding of oral microbiome assembly,gene expression,metabolites,microenvironments,virulence mechanisms,and microbe-host interfaces in the context of health and disease.However,significant knowledge gaps persist regarding community origins,developmental trajectories,homeostasis versus dysbiosis triggers,functional biomarkers,and strategies to deliberately reshape the oral microbiome for therapeutic benefit.The convergence of sequencing,imaging,cultureomics,synthetic systems,and biomimetic models will provide unprecedented insights into the oral microbiome and offer opportunities to predict,prevent,diagnose,and treat associated oral diseases.
8.Omics for deciphering oral microecology
Lin YONGWANG ; Liang XIAOYUE ; Li ZHENGYI ; Gong TAO ; Ren BIAO ; Li YUQING ; Peng XIAN
International Journal of Oral Science 2024;16(2):197-207
The human oral microbiome harbors one of the most diverse microbial communities in the human body,playing critical roles in oral and systemic health.Recent technological innovations are propelling the characterization and manipulation of oral microbiota.High-throughput sequencing enables comprehensive taxonomic and functional profiling of oral microbiomes.New long-read platforms improve genome assembly from complex samples.Single-cell genomics provides insights into uncultured taxa.Advanced imaging modalities including fluorescence,mass spectrometry,and Raman spectroscopy have enabled the visualization of the spatial organization and interactions of oral microbes with increasing resolution.Fluorescence techniques link phylogenetic identity with localization.Mass spectrometry imaging reveals metabolic niches and activities while Raman spectroscopy generates rapid biomolecular fingerprints for classification.Culturomics facilitates the isolation and cultivation of novel fastidious oral taxa using high-throughput approaches.Ongoing integration of these technologies holds the promise of transforming our understanding of oral microbiome assembly,gene expression,metabolites,microenvironments,virulence mechanisms,and microbe-host interfaces in the context of health and disease.However,significant knowledge gaps persist regarding community origins,developmental trajectories,homeostasis versus dysbiosis triggers,functional biomarkers,and strategies to deliberately reshape the oral microbiome for therapeutic benefit.The convergence of sequencing,imaging,cultureomics,synthetic systems,and biomimetic models will provide unprecedented insights into the oral microbiome and offer opportunities to predict,prevent,diagnose,and treat associated oral diseases.
9.Omics for deciphering oral microecology
Lin YONGWANG ; Liang XIAOYUE ; Li ZHENGYI ; Gong TAO ; Ren BIAO ; Li YUQING ; Peng XIAN
International Journal of Oral Science 2024;16(2):197-207
The human oral microbiome harbors one of the most diverse microbial communities in the human body,playing critical roles in oral and systemic health.Recent technological innovations are propelling the characterization and manipulation of oral microbiota.High-throughput sequencing enables comprehensive taxonomic and functional profiling of oral microbiomes.New long-read platforms improve genome assembly from complex samples.Single-cell genomics provides insights into uncultured taxa.Advanced imaging modalities including fluorescence,mass spectrometry,and Raman spectroscopy have enabled the visualization of the spatial organization and interactions of oral microbes with increasing resolution.Fluorescence techniques link phylogenetic identity with localization.Mass spectrometry imaging reveals metabolic niches and activities while Raman spectroscopy generates rapid biomolecular fingerprints for classification.Culturomics facilitates the isolation and cultivation of novel fastidious oral taxa using high-throughput approaches.Ongoing integration of these technologies holds the promise of transforming our understanding of oral microbiome assembly,gene expression,metabolites,microenvironments,virulence mechanisms,and microbe-host interfaces in the context of health and disease.However,significant knowledge gaps persist regarding community origins,developmental trajectories,homeostasis versus dysbiosis triggers,functional biomarkers,and strategies to deliberately reshape the oral microbiome for therapeutic benefit.The convergence of sequencing,imaging,cultureomics,synthetic systems,and biomimetic models will provide unprecedented insights into the oral microbiome and offer opportunities to predict,prevent,diagnose,and treat associated oral diseases.
10.Omics for deciphering oral microecology
Lin YONGWANG ; Liang XIAOYUE ; Li ZHENGYI ; Gong TAO ; Ren BIAO ; Li YUQING ; Peng XIAN
International Journal of Oral Science 2024;16(2):197-207
The human oral microbiome harbors one of the most diverse microbial communities in the human body,playing critical roles in oral and systemic health.Recent technological innovations are propelling the characterization and manipulation of oral microbiota.High-throughput sequencing enables comprehensive taxonomic and functional profiling of oral microbiomes.New long-read platforms improve genome assembly from complex samples.Single-cell genomics provides insights into uncultured taxa.Advanced imaging modalities including fluorescence,mass spectrometry,and Raman spectroscopy have enabled the visualization of the spatial organization and interactions of oral microbes with increasing resolution.Fluorescence techniques link phylogenetic identity with localization.Mass spectrometry imaging reveals metabolic niches and activities while Raman spectroscopy generates rapid biomolecular fingerprints for classification.Culturomics facilitates the isolation and cultivation of novel fastidious oral taxa using high-throughput approaches.Ongoing integration of these technologies holds the promise of transforming our understanding of oral microbiome assembly,gene expression,metabolites,microenvironments,virulence mechanisms,and microbe-host interfaces in the context of health and disease.However,significant knowledge gaps persist regarding community origins,developmental trajectories,homeostasis versus dysbiosis triggers,functional biomarkers,and strategies to deliberately reshape the oral microbiome for therapeutic benefit.The convergence of sequencing,imaging,cultureomics,synthetic systems,and biomimetic models will provide unprecedented insights into the oral microbiome and offer opportunities to predict,prevent,diagnose,and treat associated oral diseases.


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