BACKGROUND:The pathogenesis of moyamoya disease is unclear,and there is a lack of early diagnostic methods and effective medical treatments.OBJECTIVE:To identify biomarkers of moyamoya disease through machine learning,and analyze the therapeutic mechanism of Bu Huang Si Wu Tang in moyamoya disease.METHODS:Moyamoya disease gene dataset from gene expression omnibus database was retrieved.R language was used to screen differentially expressed genes and perform enrichment analysis on differentially expressed genes.Moyamoya disease biomarkers were screened using least absolute shrinkage and selection operator and support vector machine-recursive feature elimination machine learning algorithms.A diagnostic model was constructed by establishing a column chart,and its clinical utility and diagnostic value were evaluated and further validated through detecting clinical serum markers of patients with moyamoya disease.In vitro experiments were performed to observe the effect of Bu Huang Si Wu Tang on umbilical vein endothelial cells under oxygen glucose deprivation,and the main components of Bu Huang Si Wu Tang were selected for molecular docking and molecular dynamics simulation with the screened targets to explore its potential mechanism.RESULTS AND CONCLUSION:This study identified 76 differentially expressed genes,mainly enriched in immune and metabolic related pathways.Two potential biomarkers,complement factor D(CFD)and DKFZp434L192,were obtained through machine learning.The calibration curve,decision curve analysis,and clinical impact curve showed that the column chart had good predictive ability.qRT-PCR analysis showed that CFD and DKFZp434L192 expression levels were significantly upregulated in patients with moyamoya disease(P<0.001).In vitro experiments showed that Bu Huang Si Wu Tang significantly enhanced the activity and migration ability(P<0.01)of umbilical vein endothelial cells under oxygen glucose deprivation.Molecular docking results showed that all four active ingredients of Bu Huang Si Wu Tang could bind to the target site,and the dynamic simulation results further verified its binding stability.To conclude,CFD and DKFZp434L192 exhibit good diagnostic efficacy for moyamoya disease and can serve as potential diagnostic biomarkers and therapeutic targets for moyamoya disease.Bu Huang Si Wu Tang has a certain protective effect on vascular endothelial cells under ischemic conditions,which may be related to CFD.

BACKGROUND:The pathogenesis of moyamoya disease is unclear,and there is a lack of early diagnostic methods and effective medical treatments.OBJECTIVE:To identify biomarkers of moyamoya disease through machine learning,and analyze the therapeutic mechanism of Bu Huang Si Wu Tang in moyamoya disease.METHODS:Moyamoya disease gene dataset from gene expression omnibus database was retrieved.R language was used to screen differentially expressed genes and perform enrichment analysis on differentially expressed genes.Moyamoya disease biomarkers were screened using least absolute shrinkage and selection operator and support vector machine-recursive feature elimination machine learning algorithms.A diagnostic model was constructed by establishing a column chart,and its clinical utility and diagnostic value were evaluated and further validated through detecting clinical serum markers of patients with moyamoya disease.In vitro experiments were performed to observe the effect of Bu Huang Si Wu Tang on umbilical vein endothelial cells under oxygen glucose deprivation,and the main components of Bu Huang Si Wu Tang were selected for molecular docking and molecular dynamics simulation with the screened targets to explore its potential mechanism.RESULTS AND CONCLUSION:This study identified 76 differentially expressed genes,mainly enriched in immune and metabolic related pathways.Two potential biomarkers,complement factor D(CFD)and DKFZp434L192,were obtained through machine learning.The calibration curve,decision curve analysis,and clinical impact curve showed that the column chart had good predictive ability.qRT-PCR analysis showed that CFD and DKFZp434L192 expression levels were significantly upregulated in patients with moyamoya disease(P<0.001).In vitro experiments showed that Bu Huang Si Wu Tang significantly enhanced the activity and migration ability(P<0.01)of umbilical vein endothelial cells under oxygen glucose deprivation.Molecular docking results showed that all four active ingredients of Bu Huang Si Wu Tang could bind to the target site,and the dynamic simulation results further verified its binding stability.To conclude,CFD and DKFZp434L192 exhibit good diagnostic efficacy for moyamoya disease and can serve as potential diagnostic biomarkers and therapeutic targets for moyamoya disease.Bu Huang Si Wu Tang has a certain protective effect on vascular endothelial cells under ischemic conditions,which may be related to CFD.

A quartz tube reactor was designed to combine with a commercial mass spectrometer for on-line detecting the gases evolved during pyrolysis of coal and other samples with high volatile. The reliability and repeatability of this atmosphere pressure-temperature programmed pyrolysis-mass spectrum (AP-TPP-MS) system were tested by model compound and real coal sample. The results show that pyrolysis of model compound can give good response, less overlap or tailing gases evolution curves;and multi-peaks can be observed from the same gas curve of real sample. The reliability and repeatability of this system are perfect and the system can be applied to study the coals decarboxylation by comparing the CO_2 evolution curves.