1.Preliminary study on metabonomics of hypertension hyperactivity of liver yang syndrome
Yang GAO ; Yuanhui HU ; Zheng YANG ; Yuguang CHU ; Jie SHI ; Li MENG
International Journal of Traditional Chinese Medicine 2013;35(10):889-892
Objective In the present study,we use GC/MS-based metabolomics approaches to make analysis of serum metabolic profiles of healthy people and the hyperactivity of liver yang type of constitution in patients with essential hypertension.Try to establish the discriminant model,to discover biomarkers (group) of the hyperactivity of liver yang type of essential hypertension,and to explore the essential material basis of Traditional Chinese medicine syndrome theory.Methods Classified according to the guiding principles of Chinese medicine research,the hyperactivity of liver yang type of constitution in male patients with essential hypertension (n=18),as well as health volunteers (n=15) were randomly selected from Guang An Men Hospital clinic,wards and medical center in the first half of 2010,selected patients with essential hypertension requirements are not taking any drugs or Chinese herbs,or stop taking the various drugs more than one week.Extracted Venous Blood of subjects fasting for 12 hours,and serum was separated through centrifugation.Serum samples are stored and at-86℃ refrigerator.Survey and evaluate endogenous metabolism in serum samples of health control group and types of syndrome mentioned above by gas chromatograph mass spectrometry (GCMS)analysis.Then,analyze the metabolites with Partial Least Squares-Discriminant Analysis.Further use PCA to analyze the principal component factor loadings matrix analysis,and for variable scatter plot (Loading plot),significant increase or decrease the variables can be found from the figure.The combination of these variables is the lesion biomarkers group.Results Compared with the health control group,13 differentially expressed metabolites in the essential hypertension hyperactivity of liver yang type group can be identified (P<0.05).8 metabolites were up-regulated expression:Uric acid,citrate,Octadecanoic acid,Hexadecanoic acid,Octadecadienoic acid,Leucine,Cholesterol,Norvaline,and 5 metabolites were down-regulated expression:arachidonate,Oleate,Alanine,Aspartic acid,glycine.Conclusion We are incline to regard that the 13 of EH patient serum differentially expressed metabolites are EH hyperactivity of liver yang syndrome metabolic biomarkers:Uric acid,citrate,Octadecanoic acid,Hexadecanoic acid,Octadecadienoic acid,Leucine,Cholesterol,Norvaline,Arachidonate,Oleate,Alanine,Aspartic acid,glycine.
2.Research progress of traditional Chinese medicine for stem cell therapy of ischemic heart disease.
Huaqin WU ; Yuanhui HU ; Yuping ZHOU ; Yuguang CHU
China Journal of Chinese Materia Medica 2009;34(8):935-938
Regeneration myocardium by stem cell transplantartion has become a focus in research areas of cardial vascular disease. This review deals the role of traditional Chinese medicine in stem cell threapy of ischemic heart disease, such as mobilizing bone marrow stem cells, promoting stem cell proliferation, survival, induced them to differentiate into cardiomyocytes, and so on, showing good application prospects.
Drugs, Chinese Herbal
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therapeutic use
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Humans
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Medicine, Chinese Traditional
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methods
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Myocardial Ischemia
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therapy
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Stem Cell Transplantation
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methods
3.Atrial fibrillation detection using millimeter-wave radar
Hengji ZHOU ; Yihan YANG ; Yuanhui HU ; Yuguang CHU ; Xintian SHOU ; Yaping YOU ; Wenjing XUE ; Shaowei FAN ; Yong WANG ; Huiliang SHEN
Chinese Journal of Medical Physics 2024;41(1):81-87
A novel technology is proposed for non-contact and real-time detection of atrial fibrillation using millimeter-wave radar.A 60 GHz PCR millimeter wave radar is used to continuously detect the chest echo signal of the subject.After signal acquisition,I-Q signal is generated through I-Q demodulation,and the signal phase information is extracted using effective points phase trend evaluation for obtaining the signals from oscillations in the chest wall,from which the respiratory signals and cardiac signals are extracted through digital filtering for the analysis of cardiac movement.Whether the atrial fibrillation occurs or not is determined by the characteristics of atrial fibrillation wave in the time domain.The effective points phase trend evaluation for extracting more accurate signal phase information and the time-domain method for real-time atrial fibrillation detection are the innovations of the study.The experimental results show that the proposed method achieves a detection accuracy of 99.2%in clinic.