[Application and progress of data mining in study of compatibility law of traditional Chinese medicine].

Data mining is an important method to obtain the key information from a large amount of data, and it is widely applied in the research on the modernization of traditional Chinese medicine(TCM). The compatibility law of herbs is a key issue in the research of TCM prescriptions. This reflects the flexibility and effectiveness of TCM prescriptions, and it is also a crucial link to the development of TCM modernization. Therefore, it is the core purpose of the research on TCM prescriptions to find the compatibility law of herbs and clarify the scientific connotation. Data mining, as an effective method and an important approach, has formed a standardized system in the research of compatibility law of herbs, which can reveal the relationship between different Chinese herbs and summarize the internal rules in compatibility. Two hundred and twenty two effective papers were sorted out and categorized in this article. The results showed that data mining was mainly applied in finding the core Chinese herb pairs, summarizing the utility and attributes of TCM prescriptions, revealing the relationship between prescriptions, Chinese herbs and syndromes, finding the optimal dose of Chinese herbs, and producing the new prescriptions. The problems of data mining in research of herbs compatibility rules were summarized, and its development and trend in current researches were discussed in this article to provide useful references for the in-depth study of data mining in the compatibility law of Chinese herbs.

Application of an extreme learning machine network with particle swarm optimization in syndrome classification of primary liver cancer.

OBJECTIVE: By optimizing the extreme learning machine network with particle swarm optimization, we established a syndrome classification and prediction model for primary liver cancer (PLC), classified and predicted the syndrome diagnosis of medical record data for PLC and compared and analyzed the prediction results with different algorithms and the clinical diagnosis results. This paper provides modern technical support for clinical diagnosis and treatment, and improves the objectivity, accuracy and rigor of the classification of traditional Chinese medicine (TCM) syndromes. METHODS: From three top-level TCM hospitals in Nanchang, 10,602 electronic medical records from patients with PLC were collected, dating from January 2009 to May 2020. We removed the electronic medical records of 542 cases of syndromes and adopted the cross-validation method in the remaining 10,060 electronic medical records, which were randomly divided into a training set and a test set. Based on fuzzy mathematics theory, we quantified the syndrome-related factors of TCM symptoms and signs, and information from the TCM four diagnostic methods. Next, using an extreme learning machine network with particle swarm optimization, we constructed a neural network syndrome classification and prediction model that used "TCM symptoms + signs + tongue diagnosis information + pulse diagnosis information" as input, and PLC syndrome as output. This approach was used to mine the nonlinear relationship between clinical data in electronic medical records and different syndrome types. The accuracy rate of classification was used to compare this model to other machine learning classification models. RESULTS: The classification accuracy rate of the model developed here was 86.26%. The classification accuracy rates of models using support vector machine and Bayesian networks were 82.79% and 85.84%, respectively. The classification accuracy rates of the models for all syndromes in this paper were between 82.15% and 93.82%. CONCLUSION: Compared with the case of data processed using traditional binary inputs, the experiment shows that the medical record data processed by fuzzy mathematics was more accurate, and closer to clinical findings. In addition, the model developed here was more refined, more accurate, and quicker than other classification models. This model provides reliable diagnosis for clinical treatment of PLC and a method to study of the rules of syndrome differentiation and treatment in TCM.

Application and progress of data mining in study of compatibility law of traditional Chinese medicine / 中国中药杂志

Data mining is an important method to obtain the key information from a large amount of data, and it is widely applied in the research on the modernization of traditional Chinese medicine(TCM). The compatibility law of herbs is a key issue in the research of TCM prescriptions. This reflects the flexibility and effectiveness of TCM prescriptions, and it is also a crucial link to the development of TCM modernization. Therefore, it is the core purpose of the research on TCM prescriptions to find the compatibility law of herbs and clarify the scientific connotation. Data mining, as an effective method and an important approach, has formed a standardized system in the research of compatibility law of herbs, which can reveal the relationship between different Chinese herbs and summarize the internal rules in compatibility. Two hundred and twenty two effective papers were sorted out and categorized in this article. The results showed that data mining was mainly applied in finding the core Chinese herb pairs, summarizing the utility and attributes of TCM prescriptions, revealing the relationship between prescriptions, Chinese herbs and syndromes, finding the optimal dose of Chinese herbs, and producing the new prescriptions. The problems of data mining in research of herbs compatibility rules were summarized, and its development and trend in current researches were discussed in this article to provide useful references for the in-depth study of data mining in the compatibility law of Chinese herbs.

Meta-analysis of Oral Chinese Medicine for Adjuvant Treatment of Primary Hepatic Carcinoma and Screening of Basic Chinese Herbs / 中国实验方剂学杂志

Objective:To systematically evaluate the efficacy of oral Chinese herbal prescriptions combined with transcatheter arterial chemoembolization （TACE） against primary hepatic carcinoma （PHC） and screen the basic Chinese herbs，in order to provide certain reference for clinical medication. Method:The randomized controlled trials concerning the treatment of PHC with oral Chinese herbal prescriptions plus TACE were retrieved from CBM，China National Knowledge Infrastructure （CNKI），Chongqing Weipu Database for Chinese Technical Periodicals （VIP），and Wanfang Data Knowledge Service Platform.The quality of the included trials was evaluated by Cochrane handbook，and the Meta-analysis was performed using RevMan 5.3.The enumeration data were expressed by odds ratio （OR），the measurement data by mean difference （MD） or standardized mean difference （SMD），and the effect size by 95% confidence interval （CI）.The data of oral Chinese herbal prescriptions involved in trials were sorted out and subjected to association rule analysis and frequency analysis based on the Traditional Chinese Medicine Inheritance Support System （TCMISS），for exploring the basic Chinese herbs and their dosages against PHC. Result:A total of 75 randomized controlled trials were included，involving 7 406 cases. As revealed by the Meta-analysis，oral Chinese herbal prescriptions combined with TACE was significantly better than TACE alone in improving the short-term curative effect ［OR=2.05，95%CI（1.83，2.29）］，decreasing alpha fetoprotein （AFP） ［MD=-59.02，95%CI（-79.03，-39.01）］，ameliorating liver function ［SMD=-1.23，95%CI（-1.58，-0.88）］，boosting immunity ［SMD=1.08，95%CI（0.84，1.32）］，adjusting Karnofsky Performance Status （KPS） scale score ［OR=2.7，95%CI（1.11，11.02）］，elevating survival rate ［OR=2.31，95%CI（1.96，2.71）］，and reducing adverse reactions ［OR=0.38，95%CI（0.34，0.43）］.Data mining results showed that the basic Chinese herbs against PHC were Bupleuri Radix，Paeoniae Alba Radix，Atractylodis Macrocephalae Rhizoma，Poria，and Glycyrrhizae Radix et Rhizoma，with their clinical dosages listed as follows：6-15 g for Bupleuri Radix，10-15 g for Paeoniae Alba Radix，9-15 g for Atractylodis Macrocephalae Rhizoma，10-15 g for Poria，and 3-10 g for Glycyrrhizae Radix et Rhizoma. Conclusion:The oral Chinese herbal prescriptions combined with TACE produce better effects in treatment of PHC as compared with TACE alone.These five basic Chinese herbs have anti-cancer effect，and their dosages are within the ranges stipulated in 2020 edition of <italic>Chinese Pharmacopoeia.</italic>This Meta-analysis has provided certain reference for clinical medication.

Application of an extreme learning machine network with particle swarm optimization in syndrome classification of primary liver cancer / 中西医结合学报

OBJECTIVE@#By optimizing the extreme learning machine network with particle swarm optimization, we established a syndrome classification and prediction model for primary liver cancer (PLC), classified and predicted the syndrome diagnosis of medical record data for PLC and compared and analyzed the prediction results with different algorithms and the clinical diagnosis results. This paper provides modern technical support for clinical diagnosis and treatment, and improves the objectivity, accuracy and rigor of the classification of traditional Chinese medicine (TCM) syndromes.@*METHODS@#From three top-level TCM hospitals in Nanchang, 10,602 electronic medical records from patients with PLC were collected, dating from January 2009 to May 2020. We removed the electronic medical records of 542 cases of syndromes and adopted the cross-validation method in the remaining 10,060 electronic medical records, which were randomly divided into a training set and a test set. Based on fuzzy mathematics theory, we quantified the syndrome-related factors of TCM symptoms and signs, and information from the TCM four diagnostic methods. Next, using an extreme learning machine network with particle swarm optimization, we constructed a neural network syndrome classification and prediction model that used "TCM symptoms + signs + tongue diagnosis information + pulse diagnosis information" as input, and PLC syndrome as output. This approach was used to mine the nonlinear relationship between clinical data in electronic medical records and different syndrome types. The accuracy rate of classification was used to compare this model to other machine learning classification models.@*RESULTS@#The classification accuracy rate of the model developed here was 86.26%. The classification accuracy rates of models using support vector machine and Bayesian networks were 82.79% and 85.84%, respectively. The classification accuracy rates of the models for all syndromes in this paper were between 82.15% and 93.82%.@*CONCLUSION@#Compared with the case of data processed using traditional binary inputs, the experiment shows that the medical record data processed by fuzzy mathematics was more accurate, and closer to clinical findings. In addition, the model developed here was more refined, more accurate, and quicker than other classification models. This model provides reliable diagnosis for clinical treatment of PLC and a method to study of the rules of syndrome differentiation and treatment in TCM.

Significance of visual electrophysiological techniques in the early diagnosis of glaucoma / 国际眼科杂志(Guoji Yanke Zazhi)

Glaucoma is a group of diseases which can threaten and damage the optic nerve and its visual pathway, leading to visual impairment as a result. Glaucomatous optic neuropathy is a chronic disease accompanied by apoptosis of retinal ganglion cells ( RGCs ) , visual field defect and cupping of optic nerve head. The gold standard in functional glaucoma evaluation is standard automated perimetry ( SAP) , but it is often limited to the subjective feelings of the patients. Still, visual electrophysiological techniques cannot replace the conventional inspection, but with its rapid development, it has provided a new strategy for the early diagnosis of glaucoma as a supplement because it can show changes in amplitude and latency before visual field defect. Here we review three special electroretinograms and multifocal focal visually evoked potentials in the early diagnosis of glaucoma.

Enhanced hypoxia-inducible factor (HIF)-1α stability induced by 5-hydroxymethyl-2-furfural (5-HMF) contributes to protection against hypoxia.

We first reported the role of 5-hydroxymethyl-2-furfural (5-HMF) against hypoxia. Here, we studied the mechanism by using oxygen-dependent degradation domain (ODD)-Luc mice, which are a useful model to probe the stabilization of hypoxia-inducible factor 1α (HIF-1α). Compared with three other compounds that have been reported to have a role in stabilizing HIF-1α, 5-HMF caused stronger bioluminescence, which is indicative of HIF-1α stability in the brain and kidney of ODD-Luc mice. We further demonstrated that the HIF-1α protein accumulated in response to 5-HMF in the brains and kidneys of these mice, as well as in PC12 cells. Additionally, 5-HMF promoted the nuclear translocation of HIF-1α and the transcriptional activity of HIF-1, which was evaluated by detecting vascular endothelial growth factor (VEGF ) mRNA expression. These results suggest that 5-HMF stabilized HIF-1α and increased its activity. Considering the role of proline hydroxylases (PHDs) in negatively regulating HIF-1α stability, we explored whether 5-HMF interacts with the substrates and cofactors of PHDs, such as 2-oxoglutarate (2-OG), Fe(2+) and vitamin C (VC), which affects the activity of PHDs. The result revealed that 5-HMF did not interact with Fe(2+) or 2-OG but interacted with VC. This interaction was confirmed by subsequent experiments, in which 5-HMF entered into cells and reduced the VC content. The enhanced stability of HIF-1α by 5-HMF was reversed by VC supplementation, and the improved survival of mice caused by 5-HMF under hypoxia was abrogated by VC supplementation. Thus, we demonstrated for the first time that 5-HMF increases HIF-1α stability by reducing the VC content, which mediates the protection against hypoxia.

A new dibenzofuran and other constituents from Ligularia caloxantha, a Chinese medicinal plant.

A new dibenzofuran named 1,2,4-trimethyl-7,8-dimethoxy-dibenzofuran (1), together with seven known compounds, euparin (2), 2,5-diacetyl-6-hydroxy-benzofuran (3), 2-acetyl-5,6-dimethoxy-benzofuran (4), gummosogenin (5), lupeol (6), stigmasterol (7) and (E)-2,5-dihydroxy-cinnamic acid (8), were isolated from the roots of Ligularia caloxantha, a Chinese medicinal plant. The structures of the compounds were elucidated by spectroscopic methods.

Effect of yiqi huoxue recipe on cardiac function and ultrastructure in regression of pressure overload-induced myocardial hypertrophy in rats.

OBJECTIVE: To investigate the effect of Yiqi Huoxue Recipe (YHR) on the cardiac function and ultrastructure during the regression of myocardial hypertrophy induced by pressure overload in rats. METHODS: The model of myocardial hypertrophy was established by abdominal aortic banding. Eighty male Wistar rats were divided into six groups, the normal control group I (n=20), the normal control group II (n=12), the hypertension model group I (n=12), the hypertension model group II (n=12), the YHR group (n=12) and the Captopril group (n=12). The observation was carried out in the normal control group I and the hypertension model group I after 4 weeks of modeling, and the other four groups were observed after 16 weeks of modeling (12 weeks of administration). The cardiac function was measured with a multichannel biological signal analysis system, and the myocardium ultrastructure was observed by a transmission electron microscope. RESULTS: (1) Compared with the normal control group I, the systolic blood pressure and cardiac coefficient (left ventricular weight/body weight) in the model I group was higher (P<0.05, P<0.01). (2) In the YHR group, cardiac coefficient and -dp/dt(max) were lower, left ventricular systolic pressure and +dp/dt(min) were higher when compared with the model group II and the Captopril group (P<0.05 or P<0.01). In the Captopril group, only cardiac coefficient was lower when compared with the mode group II (P<0.05). (3) Compared with the normal control group II, +dp/dt(max) was higher (P<0.01) -dp/dt(max) and isovolumetric contraction time (ICT) was lower (P<0.05, P<0.01) in both the YHR group and the Captopril group. (4) Results of the myocardium ultrastructure showed edema under myocardium plasmalemma, enlarged sarcoplasmic reticulum and T tube, and significantly enlarged intercalated disc of the cardiac muscle in the model groups. In the Captopril group, the extension of sarcoplasmic reticulum and T tube as well as the pathological changes of intercalated disc were lighter, with slight edema under the myocardium plasmalemma. In the YHR group, the expansion of the sarcoplasmic reticulum was less than in the Captopril group, part of the pathological changes of intercalated discs was slightly more severe than that in the Captopril group, the dissolution of nuclear chromatin was not found, which was similar to that of the Captopril group, and no injury of the nucleus was found, either. CONCLUSION: YHR could reverse myocardial hypertrophy in rats with abdominal aortic banding and improve the systolic and diastolic function of the left ventricle. The ultrastructure of the myocardium such as arcoplasmic reticulum, intercalated disc, and cell nucleus in abdominal aortic banding rats could be partly reversed by the recipe.

[Research progress in Laggera medicinal plants].

This paper reviewed the worldwide research progresses of the genus Laggera both on phytochemical and pharmacological work in the past few decades. The main secondary metabolites of this genus are proved to be sesquitepenoids, flavonoids and phenolic acids. Phamacological investigations revealed that the certain extracts of some Laggera species possess significant bioactivities on anti-inflammation, anti-tumor and anti-viral infection. This review afforded the comprehensive description of the active components as to provide useful references to elucidate their historical clinical application on upper respiratory infection, influenza, parotitis, and recurrent herpes viral infection.

Research progress in Laggera medicinal plants / 中国中药杂志

This paper reviewed the worldwide research progresses of the genus Laggera both on phytochemical and pharmacological work in the past few decades. The main secondary metabolites of this genus are proved to be sesquitepenoids, flavonoids and phenolic acids. Phamacological investigations revealed that the certain extracts of some Laggera species possess significant bioactivities on anti-inflammation, anti-tumor and anti-viral infection. This review afforded the comprehensive description of the active components as to provide useful references to elucidate their historical clinical application on upper respiratory infection, influenza, parotitis, and recurrent herpes viral infection.