Study on the Medication Rules of Traditional Chinese Medicine Prescriptions for the Treatment of New Crown Pneumonia Based on Data Mining Technology

[Objectives]This study was conducted to analyze the medication rules of clinical prescriptions of traditional Chinese medicine decoction pieces for the treatment of novel coronavirus pneumonia(COVID-19)during the epidemic in multiple regions based on data mining technology,so as to provide a reference for the treatment of COVID-19 with traditional Chinese medicine.[Methods]The traditional Chinese medicine prescriptions used since the outbreak of COVID-19 in Hubei Province during the fight against the epidemic from February 25,2020 to February 14,2022,the traditional Chinese medicine prescriptions used by Guizhou traditional Chinese medicine expert team aiding Hubei Province,the traditional Chinese medicine prescriptions for rehabilitation and conditioning of patients in Ezhou of Hubei Province after discharge,the traditional Chinese medicine prescriptions for the prevention and treatment of COVID-19 in Guizhou Province,and the traditional Chinese medicine prescriptions for the treatment of COVID-19 collected from the end of 2019 to the present from the Chinese database of CNKI were collected as the data of this study.Excel was used to establish a database and enter it into the TCM inheritance calculation platform V3.5,and the association rules and k-means clustering algorithm were used to analyze the frequency of herbal medicines in prescriptions during the treatment of COVID-19,the frequency of four natures,five flavors,meridian distribution,and drug combinations.[Results]A total of 1859 COVID-19 patients treated with traditional Chinese medicine were included,and the proportion of males was higher than that of females,and middle-aged and elderly people were the most common group.A total of 2170 prescriptions of traditional Chinese medicine were included,involving a total of 383 traditional Chinese medicines.High-frequency medicines included poria,Radix Bupleuri,Radix Scutellariae,Herba Pogostemonis,Fructus Forsythiae,Flos Loniceraeetc.The four natures were mainly concentrated in cold,warm and neutral,and the five flavors were mainly concentrated in bitter,pungent and sweet.The herbal medicines were mainly attributed to the lungs and stomach meridians,and were mainly of heat-clearing,exterior syndrome-relieving and diuresis-promoting and damp-clearing types.A total of 24 high-frequency herbal combinations and 35 association rule were excavated,and 3 types of formulas were obtained by cluster analysis.[Conclusions]The analysis results and medicine combinations obtained in the formulas are consistent with the traditional Chinese medicine treatment theory of COVID-19 caused by wind-heat filth accompanied with damp and toxin.

Advancements in Medication Rule for Pulmonary Nodules: A Review of Current Research Progress

This paper reviewed the literature on medication rule of pulmonary nodules in recent years. It is found that contemporary doctors pay more attention to regulating Qi, clearing heat and detoxifying, eliminating phlegm, dissolving phlegm and dissipating masses. They use mild drugs, cold and warm treatments in parallel, combining the tastes of pungent, bitterness, and sweetness at the same time. The treatment focuses on the five viscera with emphasis on the lung meridian while also considering the spleen and stomach functions as well as soothing liver stagnation. This information aims to provide some reference for clinical treatment of pulmonary nodules.

Study on medication rules of Chinese herbs in the regulation of necroptosis based on network pharmacology and data mining

Objective:To analyze the basis and medication rules of Chinese herbs in the regulation of necroptosis.Methods:With the help of GeneCards,DrugBank,TTD,DisGeNET,OMIM database to collect the action targets of necroptosis,the TCMSP database to obtain the target‑related compounds and Chinese herbs,and the ADME criteria and Lipinski rule as the conditions for screening,to build the target‑compound,target‑compound‑Chinese herbs network.The information of Chinese herbal medicine's sexual taste and meridian was collected,and the drug use pattern was analyzed.The information on the property,flavor and channel tropism of Chinese herbs was collected to analyze the medication laws.Molecular docking of core targets and compounds in the network with AutoDockTools software,and PyMOL software was used to display the combinations with good docking results.Results:A total of 12 potential targets acting on necroptosis were obtained,matching to 191 candidate compounds and 366 herbal medicines.Quercetin,wogonin,triptolide,licochalcone a,ellipticine are more important and may be the main small molecule substances underlying the regulation of necroptosis.The more important Chinese herbs are Licorice,Forsythia,Salivae Miltiorrhizae,Ginkgo Leaf,Eucommia ulmoides Oliv,etc.The herbal medicines are mainly bitter and pungent,with cold and warm taste,which were attributed to the liver and lung meridians.BCL2‑beta‑sitosterol、MAPK14‑luteolin、MAPK14‑formononetin、TP53‑formononetin are better molecular docking results,which have strong docking activity.Conclusion:The study systematically analyzes the material basis of regulating necroptosis and summarizes the general rule of regulating necroptosis in Chinese medicine,which provides ideas for clinical development of agents to interfere with necroptosis.

Medication Rules of Traditional Chinese Medicine for Treating Threatened Abortion in the Early Stage of Pregnancy with Subchorionic Haematoma Based on Data Mining

Objective:Using data mining technology to explore the rules of traditional Chinese medicine(TCM)in the treatment of threatened abortion in the early stage of pregnancy with sub-chorionic haematoma(SCH).Methods:Literature of TCM in the treatment of threatened abortion in the early stage of pregnancy with SCH were retrieved from CNKI,VIP,WANFANG and Pubmed,EMBASE.The literature information database was established to be used for descriptive analysis,association rule analysis and cluster analysis of relevant data.Results:A total of 100 literatures were included,involving 114 Chinese herbs.The efficacy of Chinese herbs were mainly tonic drugs,hemostatic drugs,heat-clearing drugs,dissolving blood stasis and hemostatic drugs.The medicinal properties were mostly mild and warm,and the taste of the drug was mainly sweet,bitter and pungent.The liver meridian,spleen meridian and kidney meridian were frequently used.The commonly used drug pair combination was"Xu duan(Radix dipsaci,续断)-Tusizi(Semen Cuscutae,菟丝子)",and the core combination was"Tusizi-Xu duan-Ejiao(Donkeyhide gelatin,阿胶)-Baizhu(Atractylodes macrocephala,白术)-Dangshen(Codonopsis pilosula,党参)".Commonly used drugs for removing blood stasis and hemostasis were with Sanqi(Panax notoginseng,三七),Puhuang(cattail pollen,蒲黄),and Qiancao(Radix Rubiae,茜草).Conclusion:Data mining traditional Chinese medicine for the treatment of threatened abortion in the early stage of pregnancy with SCH clinically commonly used drug efficacy,taste,meridian,commonly used drug pairs,core combination and commonly used blood stasis hemostatic drugs,has important reference significance for the treatment of threatened abortion in the early stage of pregnancy combined with SCH.

Study on medication rules of traditional Chinese medicine for Meniere's disease based on data analysis

Objective:Study on medication rules of traditional Chinese medicine in treating Meniere's disease based on data mining technology.Methods:Computer retrieval with since establishment of the“CNKI”,“WF”,“VIP”,there have been literatures on the treatment of Meniere syndrome with Traditional Chinses medicine.Memory preprocessing in accordance with inclusion criteria.Then,EXCLE 2010,SPSS Statistics(ver.25)and SPSS Modeler(ver.18.0)were adopted respectively for frequency analysis,cluster analysis and association rules analysis.Result:A total of 133 references were included in this study,146 prescriptions,192 kinds of drugs,and the total frequency of drugs was 1702.The high frequency Meniere syndrome types were spleen deficiency and phlegm dampness syndrome,wind phlegm syndrome,gallbladder depression and phlegm disturbance syndrome,hyperactivity of liver yang syndrome,phlegm and blood stasis syndrome.The efficacy of drug frequency≥25 were summarized as follows,antiasthmatic drugs for relieving phlegm and relieving cough,diuresis-removing dampness,Tonic drugs,etc.High frequency meridian of drugs are:lung,liver,spleen,etc.High frequency drug properties are:temperature,cold,flat etc.High frequency drug taste:bitter,sweet,pungent,etc.Core drugs:Pinellia,Atractylodes,Poria,Gastrodia,etc.The main prescriptions werealisma soup,Banxia Baizhu Tianma Decoction,Zhengan Xifeng Decoction and Xiaochaihu Decoction.Conclusion:In this study,data mining was used to sort out the treatment of Meniere's disease by traditional Chinese medicine.It was found that the treatment of Meniere's disease was mainly to calm the liver and strengthen the spleen,supplemented by regulating qi and activating blood,clearing heat and opening orifices,tonifying deficiency and tranquilizing mind.

Study on the medication rules of traditional Chinese medicine in the treatment of sleep disorder after stroke based on data mining

Objective:To explore the medication rule of Traditional Chinese Medicine(TCM)in the treatment of sleep disorder after stroke by using data mining technology.Methods:A computer search was used to search the electronic database of clinical literature on the treatment of sleep disorders after stroke by TCM from January 2000 to January 2021.Excel was used to establish the database,and the prescription information was described and analyzed statistically.Using IBM SPSS Modeler 18.0 software,Apriori algorithm was used for TCM association analysis,and IBM SPSS 22.0 software was used for systematic cluster analysis of high-frequency TCM.Results:A total of 67 literatures were included,covering 131 traditional Chinese medicines.The medecines with a higher frequency of sodium use include Ziziphi Spinosae Semen(Suanzaoren),Angelicae Sinensis Radix(Danggui),Ligusticum(Chuanxiong),liquorice(Gancao),Poria cocos(Fuling),and so on.From the effect point of view,deficiency-tonifying medicine,sedative medicine and blood-activating and stasis-removing medicine are commonly used.The medicinal properties are mainly cold,mild and warm.The main medicine flavor are sweet and bitter.The medicines mostly belong to the liver,heart and spleen Meridian.Thirty-three association rules were obtained for medicine pairs and medicine groups from the correlation analysis,and the core combinations were"Ziziphi Spinosae Semen(Suanzaoren)-Tuber fleeceflower stem(Yejiaoteng)","Ziziphi Spinosae Semen(Suanzaoren)-Polygala(Yuanzhi)","Ziziphi Spinosae Semen(Suanzaoren)-Cortex albiziae(Hehuanpi)"and"Angelicae Sinensis Radix(Danggui)-Radix bupleuri(Chaihu)-Radix Paeoniae Alba(Baishao)"and so on.Seven medicine aggregation groups were obtained by medicine cluster analysis.Conclusion:In the treatment of sleep disorder after stroke by TCM,the main method is to calm the heart and mind.Meanwhile,according to different syndrome types,the treatment methods of tonifying the heart and spleen,nourishing the liver and kidney,soothing the liver and softening the liver,clearing heat and resolving phlegm,nourishing the blood and promoting blood circulation are selected,which provide certain reference for clinical treatment.

Professor Zhang Hongchun's medication rule in treating patients with stable chronic obstructive pulmonary diseases

Based on the Traditional Chinese Medicine Inheritance Support System(TCMISS),the medication rule of Professor Zhang Hongchun in treating patients with chronic obstructive pulmonary diseases(COPD)in stable period was carried out.The prescriptions of Professor Zhang Hongchun in treating COPD patients in stable period were collected and analyzed by frequency statistics,association rules and complex system entropy clustering.A total of 111 prescriptions were screened out,including 106 kinds of traditional Chinese medicine,which were mainly warm,cold and flat,and mainly sweet,bitter and pungent.The meridians were mostly attributed to lung,spleen,liver and kidney meridians.34 core combinations of drugs were extracted,and 38 association rules with confidence level of one were obtained.Three new prescriptions were obtained.The core prescriptions were:Angelicae Sinensis Radix(15g),Pseudostellariae Radix(30g),Cornus Officinalis Sieb Et Zucc(15g),Schisandrae Chinensis Fructus(15g),Farfarae Flos(15g),Asteris Radix Et Rhizoma(15g),Poria Cocos(Schw.)Wolf(15g),Perillae Fructus(15g),Perilla Frutescens(15g),Ephedra Herba(10g),Licorice(3g).Professor Zhang Hongchun's treatment methods of COPD patients in stable stage are to invigorate lung,spleen and kidney,and to stop cough,eliminate phlegm and asthma,promote Qi,activate blood circulation and dissipate blood stasis.

Study on prescription and medication rules of Hua Baojin for treatment of colorectal cancer based on data mining

Objective:To study the prescription and medication rule of Professor Hua Baojin in the treatment of colorectal cancer through data mining,so as to provide reference for clinical treatment of colorectal cancer. Methods:The outpatient medical records of Professor Hua Baojin from June 2015 to October 2020 in Guang’anmen Hospital,China Academy of Chinese Medical Sciences were collected. TCM Inheritance Support Platform(V2.5)was used to analyze high-frequency drugs,drug properties,flavors,channel tropism,common drug combinations,core combinations and new prescriptions. Results:A total of 500 prescriptions were included,involving 222 traditional Chinese medicines and 38 high-frequency(≥100)medicines,including Atractylodes,Poria cocos,ginger,etc. The most common medicinal properties of drugs were warm,cold and mild,and flavors were sweet,bitter and pungent,channel tropism included spleen,stomach,liver and lung meridians. 36 groups of common drug combinations and 20 association rules were obtained by data mining,and 18 core combinations and 9 new prescriptions were evolved.Conclusion:Professor Hua Baojin takes recuperating spleen and stomach as the core in the treatment of colorectal cancer,attaching importance to regulating the rise and fall of qi,adding and subtracting on the basis of Xiangsha Liujunzi Decoction,flexibly selecting the drugs of dispelling blood stasis,resolving phlegm,detoxification and loose knots,and using both cold and warm in the prescription,tonifying and reducing at the same time.

A study of TCM master Yan Zhenghua’s medication rule in prescriptions for digestive system diseases based on Apriori and complex system entropy cluster

Objective:To explore Yan Zhenghua’s drug selection rule for treating digestive system diseases using data mining.Methods:The 609 medical records of digestive system diseases treated by Yan Zhenghua were collected and the herbs in these recipes were examined using a data mining technique.The correlativity between herb pairs and association rules was studied using an Apriori algorithm and the correlativity among multi-herbs was studied using a complex system entropy cluster technique.Results:Yan Zhenghua’s treatment of digestive system diseases featured 15 herbs prescribed at least 159 times each,22 herb pairs prescribed at least 155 times each,and eight frequently used herb core combinations.A confidence greater than 0.91 and a support level greater than 20%were achieved using the modified mutual information method.Conclusion:The data mining results conformed to findings from clinical practice.The data mining method is a valuable technique with which to study the experience of famous,elderly traditional Chinese medicine physicians.

A study of medication rules of traditional Chinese medicine in the treatment of pre diabetes based on data mining

Background:To summarize the concerted application and prescription rules of traditional Chinese medicine in the treatment of pre diabetes.Methods:Microsoft Excel 2010 was used to summarize the categories,nature,flavour and channel tropism of drugs.The cluster analysis of high-frequency drugs was carried out by SPSS 22.0,and the association rules of high-frequency drugs were analyzed by Apriori algorithm provided by SPSS modeler 14.0.Results:One hundred and forty-six references were included,including 153 prescriptions and 131 drugs.Their frequency of use is listed in the following order.The top 3 categories of drugs were“Tonifying,Heat-Clearing”,diuresis and“Diffusing Dampness”drugs.The top 5 drugs were Huangqi(Astragali radix),Fuling(Poria),Huanglian(Coptidis rhizoma),Shanyao(Dioscoreae rhizoma),Gegen(Puerariae lobatae radix).The top 3 channel tropism of drugs were spleen,stomach and lung.The top 3 nature of drugs were cold,warm and calm.The top 3 flavour of drugs were sweet,bitter and pungent.The cluster analysis of high-frequency drugs showed that it could be classified into 4 categories:“Benefiting Qi”for promoting production of fluid,“Clearing Heat”and“Eliminating Dampness”,“Nourishing Yin”and“Clearing Heat”,and“Invigorating Spleen”for“Diffusing Dampness”.The results of association rule analysis showed that the combination with the highest degree of confidence and support was Poria-Chenpi(Citri reticulatae pericarpium)-Banxia(Pinelliae rhizoma)-Baizhu(Atractylodis macrocephalae rhizoma)and the combination with the highest frequency was Astragali radix-Puerariae lobatae radix.Conclusion:The pre diabetes is due to deficiency.The disease location is spleen and stomach and the pathological factor is phlegm-damp,that is why benefiting qi and invigorating spleen is regarded as the key link of clinical treatment.

Analysis of ZHENG Yuling's Medication Rules in the Syndrome Differentiation and Treatment of Cervical Cancer

Objective:To analyze the medication rules of ZHENG Yuling in the treatment of cervical cancer,and provide a basis for the clinical practice of Chinese medicine for the treatment of cervical cancer.Methods:The data of patients with cervical cancer treated by ZHENG Yuling in the First Hospital Affliated to Henan Univer-sity of Chinese Medicine from March 26,2017 to January 5,2021 were collected and the medication rules were analyzed.Results:Totally 143 cases were included,and the most frequently used prescriptions were Wuling Powder(五苓散),Simiao Powder(四妙散),Danggui Shaoyao Powder(当归芍药散),Shuyu Pill(薯损丸),Qingxin Lianzi Decoetion(清心莲子饮),Bazhen Decoction(八珍汤),etc.With statistics of the efficacy,all Chinese materia medica were divided into 19 categories,and their properties were mainly warm,mild and cold;the flavors of medicine were mainly sweet,pungent and bitter;the meridian tropism mainly ineludes the lung,liver,spleen and stomach.After cluster analysis and factor analysis,15 common factors were extracted;through the analysis of association rules,14 groups of Chinese materia medica combinations with high frequency associ-ation strength were obtai ned.Conclusion:ZHENG Yuling believes that the pathogenesis of cervical cancer is not only related to disorder between Chong and conception Channels due to the intermingling of dampness,tox-icity,blood stasis,and phlegm but also retention of urine due to qi stagnation and water retention.The direct disease location is in the uterus and indirect location may involve the lung,liver,spleen and kidney according to the development of disease,accompanying symptoms and the different constitutions of the patients.It is advo-cated that attention should be paid to not only removing dampness,detoxification,removing blood stasis,and re-ducing phlegm,but also regulating qi,opening the blockage,promoting water flow.At the same time,the spleen and stomach should be protected,and tonification and purgation should be applied in combination.

Based on data mining, the study on the medication rule of Chinese patent medicine for constipation

To analyze the medication rule of Chinese patent medicine compound for constipation by data mining,and to provide reference for the treatment of constipation.Methods:The Chinese patent medicines for constipation in the Pharmacopoeia of the People’s Republic of China(2020)and Chinese patent medicine prescription database of yaozhi.com(https://db.yaozh.com/chufang)were collected and sorted.The prescriptions and drug composition were input into Excel2010.ategories,nature,flavour and channel tropism of drugs were analyzed by using ancient and modern medical case cloud platform(V2.3.5).The cluster analysis of high-frequency drugs was carried out by SPSS 22.0,and rules of high-frequency drugs were analyzed by Apriori algorithm provided by SPSS modeler 18.0.Results:Two hundred and thirty-six Chinese patent medicine prescriptions that met the requirements were collected,containing 349 Chinese medicines in total,with a total frequency of 2,277.The drugs with frequency≥25 times were high-frequency drugs,with a total of 24 flavours,and the top 5 were Dahuang(Rhei radix et rhizoma),Huangqin(Scutellariae radix),Gancao(Glycyrrhizae radix et rhizoma),Huanglian(Coptidis rhizoma)and Bohe(Menthae haplocalycis herba).The top 3 frequency of efficacy of high-frequency drugs were“Heat-Clearing(remove heat from the body surface and inside)”drugs,“Purgating(to promote excretion of stools)”drugs and“Reinforcing”(to supplement the body’s lack of“Qi,Blood,Yin and Yang”)drugs.The nature of high-frequency drugs were cold,warm and flat.The top 3 flavour of the high frequency drugs were bitter,spicy and sweet.The top 4 channel tropism of high-frequency drugs were“Spleen”,“Stomach”,“Lung”,“Large intestine”.According to the association rule,11 drug pairs were obtained,and the core drug pairs were Zhizi(Gardeniae fructus)-Rhei radix et rhizoma,Huangbo(Phellodendri chinensis cortex)-Rhei radix et rhizoma.Four new methods were obtained based on cluster analysis.Conclusion:Chinese patent medicine has a certain regularity in the treatment of constipation.This paper can provide some references for the clinical treatment of constipation with Chinese medicine.

An Analysis of Medication Rules of Chinese Medicine for Restless Legs Syndrome Based on Data Mining

Objective: Based on data mining, to explore the medication rules of Chinese medicine for the treatment of restless legs syndrome(RLS). Methods: The CNKI, WANFANG, and VIP were taken as data sources, and "restless legs syndrome, RLS" as the key words, and "Chinese medicine, Chinese materia medica, traditional Chinese medicine(TCM), traditional Chinese and Western medicine" as sub key words, the data was extracted from the journals and literature related to the treatment of RLS by TCM from the establishment of the database to 2020, and data mining techniques(frequency analysis, cluster analysis, association rules) were used to analyze the core drugs and drug pair(group) rules. Results: A total of 87 prescriptions met the requirements of this study, involving 142 Chinese herbal medicines. The top 5 Chinese herbal medicines with a higher frequency of use were Radix Paeoniae Alba, Radix Glycyrrhizae, Radix Angelicae Sinensis, Fructus Chaenomelis and Radix Astragali seu Hedysari. The four Qi(气) of the medicine were mainly warm and neutral, the five flavors were mainly sweet, bitter, and pungent. The main channels of the meridian were mainly the liver meridian, spleen meridian and heart meridian. The medication categories were mainly tonifying deficiency herbs, blood activating and removing blood stasis herbs, and eliminating wind and dampness herbs. The association rule analysis yielded 24 Chinese medicine combinations with high support, and the hierarchical cluster analysis yielded a total of 5 clusters. Conclusion: TCM treatment of RLS is based on tonifying deficiency herbs, especially to replenish Qi and blood throughout the course of the disease, supplemented by herbs for promoting blood circulation and removing blood stasis, and herbs for eliminating wind and dampness, as well as combined with herbs for reliving superficies and herbs for calming the liver to stop the wind.

Analysis on medication rules of traditional Chinese medicine for postpartum abdominal pain

Background:To explore the medication rules in traditional Chinese medicine for treating postpartum abdominal pain by using data mining technology.Methods:First,according to inclusion and exclusion criteria,the prescriptions for treating postpartum abdominal pain were collected and screened by referring to the Dictionary of Traditional Chinese Medicine Prescriptions,CNKI,Wanfang,Vip database,Chaoxing database,CBM and other databases.Then,the traditional Chinese medicinal materials were analyzed by ancient and modern medical cases cloud platform.Results:295 first prescriptions were included,involving 248 kinds of traditional Chinese medicine,and the usage frequency of traditional Chinese medicine reached 2,189 times.The efficacy of the top 22 herbs with the highest use frequency is mainly tonic drugs and drugs for promoting blood circulation and removing blood stasis,mainly with the nature of warmness and spiciness,and the channel tropisms mainly include liver meridians,spleen meridians,and heart meridians.The association rule analysis shows 17 high-frequency traditional Chinese medicine combinations with the support≥0.1 and the confidence≥0.8.Three new drug combinations were obtained through cluster mining;both of them took supplementing qi and nourishing blood,promoting blood circulation,and removing stasis as the main treatments.Conclusions:The basic principle of treatment is strengthening the body’s resistance to eliminate pathogenic factors.Therefore,when treating postpartum abdominal pain to promote postpartum recovery,it mainly combines the drugs for benefiting Qi and nourishing blood,invigorating blood circulation,and eliminating stasis.

Artificial Intelligence and Network Pharmacology Reveal the Medication Rules of Professor Wang Yu-Ying in the Treatment of Climacteric Syndrome

Objective: The objective of this study was to explore the medication rules and academic ideas of Professor Wang Yu-Ying in the treatment of climacteric syndrome(CLS) and to predict new prescriptions. Materials and Methods: The characteristics of frequency, clustering, four properties, and five flavors were analyzed, and new prescriptions were predicted through an artificial intelligence(AI)-based method. The potential pathways of new prescriptions were explored through network pharmacology-based analysis. Results: The top 16 medicinals used by Professor Wang Yu-Ying in the treatment of CLS included Danggui, Longgu, Muli, Fuling, Chuanxiong, Gancao, Xiangfu, and Tusizi. The AI method was applied to predict the basic prescription for treating CLS: Danggui 15 g, Duanlonggu 30 g, Duanmuli 30 g, Fuling 28 g, Chuanxiong 10 g, Gancao 6 g, Xiangfu 12 g, Tusizi 14 g, etc., Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses showed that the pathogenesis of CLS might be related to the estrogen pathway, involving typical steroid responses. Conclusions: This study summarized Professor Wang's medication experience in the treatment of CLS based on the data mining of clinical diagnoses and treatment cases. The AI method was used to predict the new prescription of CLS treatment, which was found to be reasonable by network pharmacology studies on its multi-target and multi-pathway mechanisms.

A Data Mining-Based Study on Medication Rules of Chinese Herbs to Treat Heart Failure with Preserved Ejection Fraction

Objective:To summarize the medication rules of Chinese herbs to treat heart failure with preserved ejection fraction(HFPEF)based on data mining and to provide references for clinical utilization.Methods:The China National Knowledge Infrastructure(CNKI),Wanfang database(Wanfang),VIP database(VIP),Chinese Biomedical Literature(CBM),PubMed,Embase,and Cochrane Library databases were searched from inception to October 2021 to identify relevant literature on treating HFPEF with Chinese herbs.Microsoft Excel 2019 was used to set up a database,and then,association rule analysis and hierarchical cluster analysis were performed by using apriori algorithm and hclust function respectively in R-Studio(Version 4.0.3).Results:A total of 182 qualified papers were included,involving a total of 92 prescriptions,130 Chinese herbs,and 872 individual herbs prescribed,with an average of 9.5 herbs per prescription.The six most frequently prescribed herbs were Astragali Radix(Huangqi),Salviae Miltiorrhizae Radix Et Rhizoma(Danshen),Poria(Fuling),Glycyrrhizae Radix Et Rhizoma(Gancao),Cinnamomi Ramulus(Guizhi),and Ginseng Radix Et Rhizoma(Renshen).There were 35 herbs used more than 5 times,involving 11 efficacy categories.The top three categories were deficiency-tonifying herbs,blood-activating and stasis-removing herbs,and dampnessdraining diuretic herbs.The most commonly used herbs were mainly warm and sweet.The primary meridian tropisms were Lung Meridian,Heart Meridian and Spleen Meridian.Association rule analysis yielded 26 association rules,such as Astragali Radix(Huangqi)&Salviae Miltiorrhizae Radix Et Rhizoma(Danshen),Poria(Fuling),Cinnamomi Ramulus(Guizhi)&Atractylodis Macrocephalae Rhizoma(Baizhu).Hierarchical cluster analysis yielded four herb classes,and their functions were mainly qi-replenishing and yang-warming,bloodactivating and diuresis-inducing.Conclusions:HFPEF is the syndrome of root vacuity and tip repletion,and its core pathogenesis is"deficiency","stasis",and"wafer",with"deficiency"being the most principal,which is closely related to Xin(heart),Fei(Lung),and Pi(Spleen).The treatment of this disease occurs by improving qi,warming yang,activating blood and inducing diuresis.Astragali Radix(Huangqi)with Salviae Miltiorrhizae Radix Et Rhizoma(Danshen)is the basic combination of herbs applied.

Analysis on oral medication rules of traditional Chinese medicine prescriptions for prevention of COVID-19

Objective:To analyze the medication rules of traditional Chinese medicine(TCM)preventive oral prescriptions for COVID-19.Methods:The preventive oral prescriptions for COVID-19 published by national and provincial health and wellness committees,administrations of TCM,medical institutions at all levels,medical masters and Chinese medicine experts were collected to establish a database,manual screening was carried out according to the inclusion and exclusion criteria,and frequency statistics,association rule analysis.The mutual information method,entropy hierarchical clustering and other methods were improved through Excel and the TCM inheritance auxiliary platform V2.5 to mine the rules and characteristics of medication.Results:The selected 157 prescriptions contained a total of 130 TCMs.The top five TCMs with the highest use frequency were Glycyrrhizae Radix et Rhizoma(86),Astragali Radix(80),Lonicerea Japonicae Flos(70),Atractylodis Macrocephalae Rhizoma(62),Saposhnikoviae Radix(60).In accordance with TCM efficacy classification,most of them were medicines for qi-tonifying(279),followed by medicines for clearing heat and drying dampness(163),dispelling pathogenic wind-cold(126),resolving dampness(111),as well as dispelling pathogenic wind-heat(99).The characteristics of four-natures of the selected medicines are as follows:most of them were cold(59),followed by warm(38)and mild(21).In terms of fivetaste,most of them were sweet(26)and acrid-and-bitter(24),followed by sweet-and-bitter(20),bitter(20)and acrid(15).For the meridian attribution,the five-zang organs and six-fu organs were all involved,most of them attributed to lung meridian(80),followed by stomach meridian(57)and spleen meridian(40).Based on association rule analysis,12 commonly used medicine combinations with two or three TCMs were found.The commonly used medicinal pairs included Astragali Radix and Saposhnikoviae Radix(51),Astragali Radix and Atractylodis Macrocephalae Rhizoma(46),Atractylodis Macrocephalae Rhizoma and Saposhnikoviae Radix(43),Astragali Radix and Atractylodis Macrocephalae Rhizoma and Saposhnikoviae Radix(38),Forsythiae Fructus and Astragali Radix(37),and so on.In addition,14 core combinations of medicines were obtained by complex system entropy cluster analysis,on this basis,six new prescriptions were screened out based on unsupervised entropy hierarchical clustering analysis.According to The Catalogue of Edible Traditional Chinese Medicinal Materials,Traditional Chinese Medicinal Materials for Health Food,and New Resources of Food published by National Health Commission of the People’s Republic of China,there are 35 species belonging to the group of edible traditional Chinese medicinal materials,20 species belonging to the group of new resources of food,31 species belonging to the group of traditional Chinese medicinal materials for health food,19.11%of the preventive oral prescriptions for COVID-19 were composed of the medicines belonging to the above three groups.Besides,there are 11 toxic species,and 24.84%of the preventive oral prescriptions for COVID-19 contained toxic TCMs.Conclusion:We found that invigorating qi and resolving dampness were the main treatment used to prevent for COVID-19,combined with the methods for strengthening vital energy and eliminating pathogenic factors.Most of the preventive oral prescriptions for COVID-19 were treated in lung,spleen and stomach meridians.In the process of selecting prescriptions and using TCMs to prevent for COVID-19,the safety of preventive medicines was also emphasized.And the theory of"Preventive Treatment of Disease"was embodied in these preventive oral prescriptions for COVID-19.For the prescriptions containing toxic TCMs,special attention should be paid to their safety in clinical application.

Integrated data mining and network pharmacology to discover a novel traditional Chinese medicine prescription against diabetic retinopathy and reveal its mechanism

Background:Diabetic retinopathy(DR)is currently the leading cause of blindness in elderly individuals with diabetes.Traditional Chinese medicine(TCM)prescriptions have shown remarkable effectiveness for treating DR.This study aimed to screen a novel TCM prescription against DR from patents and elucidate its medication rule and molecular mechanism using data mining,network pharmacology,molecular docking and molecular dynamics(MD)simulation.Method:TCM prescriptions for treating DR was collected from patents and a novel TCM prescription was identified using data mining.Subsequently,the mechanism of the novel TCM prescription against DR was explored by constructing a network of core TCMs-core active ingredients-core targets-core pathways.Finally,molecular docking and MD simulation were employed to validate the findings from network pharmacology.Result:The TCMs of the collected prescriptions primarily possessed bitter and cold properties with heat-clearing and supplementing effects,attributed to the liver,lung and kidney channels.Notably,a novel TCM prescription for treating DR was identified,composed of Lycii Fructus,Chrysanthemi Flos,Astragali Radix and Angelicae Sinensis Radix.Twenty core active ingredients and ten core targets of the novel TCM prescription for treating DR were screened.Moreover,the novel TCM prescription played a crucial role for treating DR by inhibiting inflammatory response,oxidative stress,retinal pigment epithelium cell apoptosis and retinal neovascularization through various pathways,such as the AGE-RAGE signaling pathway in diabetic complications and the MAPK signaling pathway.Finally,molecular docking and MD simulation demonstrated that almost all core active ingredients exhibited satisfactory binding energies to core targets.Conclusions:This study identified a novel TCM prescription and unveiled its multi-component,multi-target and multi-pathway characteristics for treating DR.These findings provide a scientific basis and novel insights into the development of drugs for DR prevention and treatment.

A study on the rule of Chinese medicine use against influenza virus based on data mining

Background:To summarize the rules of the use of traditional Chinese medicine against influenza virus in the high-quality literatures of core journals,and to provide guidance for the prevention and treatment of influenza.Methods:Excel 2010 and ancient and modern medical case cloud platform(2.5V)were used to summarize the categories,nature,flavour and channel tropism of drugs.The cluster analysis of high-frequency drugs was carried out by SPSS 22.0,and the association rules of high-frequency drugs were analyzed by Apriori algorithm provided by SPSS modeler 18.0.Results:One thousand one hundred and thirty-one articles from core journals were retrieved and 135 articles were screened out,including 109 prescriptions and 170 drugs,with a total frequency of 1,655 times.The 3 most frequently appeared herbs were Gancao(Glycyrrhizae radix et rhizoma),Jinyinhua(Lonicerae japonicae flos)and Lianqiao(Forsythiae fructus).The top 3 efficacy were“Heat-Clearing(remove heat from the body surface and inside)”drugs,drugs for“Relieving Exterior Disorder(treat fever,chills and headaches caused by pathogenic substances in the air)”,and“Phlegm Relieving Cough Antiasthmatic Medicine(relieves respiratory cough and sputum symptoms)”drugs.The top 3 nature of drugs were cold,warm and flat.The top 3 flavour of drugs were bitter,spicy and sweet.The top 5 channel tropism of drugs were“Lung”,“Stomach”,“Heart”,“Spleen”,“Liver”.Association rule yields 20 drug pairs,Jingjie(Schizonepetae herba),Forsythiae fructus,Lonicerae japonicae flos,Niubangzi(Arctii fructus),Mahuang(Ephedrae herba)and Glycyrrhizae radix et rhizoma were commonly used concerted application;four new methods were obtained by cluster analysis.Conclusion:The use of traditional Chinese medicine against influenza virus has a certain regularity,which provides an important reference value for the prevention and treatment of influenza.

Based on the national patent database to explore the rule of traditional Chinese medicine in the treatment of hyperlipidemia

Objective:To explore the medication law of traditional Chinese medicine compound patent for hyperlipidemia,and to provide reference for the research and development of traditional Chinese medicine new drugs for clinical treatment of hyperlipidemia.Methods:All compound TCM patents related to the treatment of hyperlipidemia were searched and extracted from the national patent database(http://epub.sipo.gov.cn)from the establishment of the database to 10st,March 2021.The data was established by the TCM Inheritance Support System(V2.5)and Microsoft Excel 2010 Softwore,and used to conduct TCM syndromes,frequency statistics,four nature and five flavors of traditional Chinese medicine,meridian attribution statistics.IBM SPSS statistics 20 software was used for drug clustering analysis,IBM SPSS modeler 18.2.2 software was used for association rules and web visualization analysis.Results:Totally 284 compound TCM patents were included,involving 577 kinds of Chinese medicine,and the most common syndrome was Yin deficiency of liver and kidney syndrome(74 times,accounting for 26.06%).The most ten common Chinese materiamedica was Hawthorn,Salvia miltiorrhiza,Alismaorientalis,Cassia seed,Polygonummultiflorum,Licorice,Poriacocos,chinese rhubarb,dried tangerine peel,Radix Paeoniae Alba.The top three appeared frequently in drug categories were tonifying deficiency medicine,activating blood-circulation and dissipating blood-stasis medicine,and heat-clearing medicine,respectively.The top two of its drug properties were warm and cold;the top three drug tastes were sweet,bitterness and pungent;the top two meridians were liver and spleen meridian,respectively.Seven drug groups were obtained by cluster analysis,and 16 were obtained by association rule analysis,including 5 drug pairs and 11 three drug groups.Conclusion:Through the data mining of the patent of traditional Chinese medicine compound prescription for regulating and treating hyperlipidemia,it is concluded that the fundamental pathogenesis of the disease is deficiency of viscera function and obstruction of phlegm and blood stasis.The clinical methods are tonifying the liver and kidney,activating blood circulation and removing stasis,resolving phlegm and removing dampness.Traditional Chinese medicine is mostly used for tonifying deficiency,activating blood circulation,removing stasis,resolving phlegm and removing dampness.This paper provides a reference for the research and development of traditional Chinese medicine for hyperlipidemia.