Field Of Traditional Chinese Medicine Research Articles

Traditional Chinese Medicine (TCM) safety evaluation and pharmacovigilance

<p indent="0mm">In recent years, there has been an increase in the number of adverse reactions/events associated with Traditional Chinese Medicine (TCM). This could be due to the passive state of the safety and risk management of TCM, which has not only led to adverse effects but also restricted the healthy and long-term development of industrial disciplines in the field of TCM. To overcome the problems associated with the safe use of TCM, we propose to speed up the establishment of a pharmacovigilance technology system in line with the characteristics of TCM, and ensure the transformation of TCM safety risk management from a passive response to active prevention and control at the earliest. Therefore, this paper systematically discusses: (1) The basic context and issues related to drug safety, (2) main challenges in the safe clinical use of TCM, and (3) pivotal pharmacovigilance methods and approaches applicable for Chinese medicine products. Drug-induced liver injury (DILI) triggered by <italic>Polygonum multiflorum</italic> and other TCMs is a current worldwide concern. Thus, we established an integrated pharmacovigilance approach of “objective identification-mechanism analysis-risk prevention and control” to solve this problem. The established pharmacovigilance technology system applied an “integrated evidence chain-based causality evaluation method” and “three-level diagnostic criteria” for the causality assessment of DILI. A new toxicology evaluation model and method, named as “disease-syndrome-based toxicology”, was developed for the safety evaluation of TCM. This system was designed for the prevention and control of TCM safety risks based on the identification of susceptible individuals, control of factors that enhance susceptibility to adverse reactions, and clinical precision medicine. Moreover, this system enables multi-source data fusion, sharing, and co-creation for DILI active monitoring and evaluation to provide data support for safety supervision and clinical drug decision making. Additionally, it provided the first online safe drug information inquiry platform, named “Inquiring Drug Safety”, for online data sharing and co-creation. Moreover, it helped construct a new model for the prevention mechanisms of TCM safety risks in people. The proposed system has been successfully used in the formulation of strategies to prevent and control safety risks of TCM and related preparations, such as <italic>Polygonum multiflorum</italic> and Rhubarb. Furthermore, this system led to the development of the first technical standard for the safe use of TCM: “Guidelines for safe use of Polygoni Multiflori Radix”. In conclusion, the established pharmacovigilance technology system overcomes the problems of causality evaluation, as well as risk prevention and control of DILI caused by TCM. Furthermore, it supports the clinical rational and safe use of TCM, and makes important contributions to ensure the healthy and sustainable development of TCM disciplines and its industry.

Application of oscillating chemical fingerprint technology combined with mathematical analysis method in quality control analysis of traditional Chinese medicine and food

Oscillating chemical fingerprint is a nonlinear dynamic fingerprint technology that reflects the overall redox activity of the entire system based on potential-time changes in multi-stage chemical reactions. This article summarizes the application of oscillating chemical fingerprint technology combined with mathematical analysis method in the qualitative and quantitative analysis of traditional Chinese medicine and food in recent years, including similarity analysis, principal component analysis, cluster analysis and other qua-litative analysis methods, as well as linear, logarithmic, exponential, polynomial, multivariate analysis and other quantitative analysis methods, so as to provide meaningful information for further quality control analysis of the oscillation chemical fingerprint technology in the field of traditional Chinese medicine and food.

Cordycepin Attenuates Palmitic Acid-Induced Inflammation and Apoptosis of Vascular Endothelial Cells through Mediating PI3K/Akt/eNOS Signaling Pathway.

A well-known medicinal mushroom in the field of traditional Chinese medicine, Cordyceps sinensis, is a rare natural-occurring entomopathogenic fungus, and it typically grows at high altitudes on the plateau of the Himalayan. Previous studies indicated that cordycepin, the main bioactive chemical of Cordyceps sinensis, has very potent anticancer, anti-oxidant and anti-inflammatory activities. However, its protective effects against atherosclerotic changes in vascular endothelial cells have not been fully elucidated. In this study, we showed that pretreatment with cordycepin significantly attenuated palmitic acid (PA)-induced cytotoxicity, reactive oxygen species (ROS) generation, and inflammatory responses. We found that PA decreased phosphorylation of Akt, eNOS, and bioavailability of nitric oxide (NO), which in turn activated NF-[Formula: see text]B and the downstream inflammatory responses. All these detrimental events were markedly blocked by pretreatment with cordycepin. Moreover, cordycepin ameliorated destabilization of mitochondrial permeability, cytosolic calcium rises, and apoptotic features caused by PA. In addition, all these anti-inflammatory and anti-apoptosis effects of cordycepin were found to be inhibited by the PI3K and eNOS inhibitor, suggesting that its anti-atherosclerotic effects may partially be mediated by the PI3K/Akt/eNOS signaling pathway.

The Impact of Artificial Intelligence on Traditional Chinese Medicine.

Traditional Chinese Medicine (TCM) is a well-established medical system with a long history. Currently, artificial intelligence (AI) is rapidly expanding in many fields including TCM. AI will significantly improve the reliability and accuracy of diagnostics, thus increasing the use of effective therapeutic methods for patients. This systematic review provides an updated overview on the major breakthroughs in the field of AI-assisted TCM four diagnostic methods, syndrome differentiation, and treatment. AI-assisted TCM diagnosis is mainly based on digital data collected by modern electronic instruments, which makes TCM diagnosis more quantitative, objective, and standardized. As a result, the diagnosis decisions made by different TCM doctors exhibit more consistency, accuracy, and reliability. Meanwhile, the therapeutic efficacy of TCM can be evaluated objectively. Therefore, AI is promoting TCM from experience to evidence-based medicine, a genuine scientific revolution. Furthermore, huge and non-uniform knowledge on formula-syndrome relationships and the combination rules of herbal TCM formulae could be better standardized with the help of AI analysis, which is necessary for the clinical efficacy evaluation and further optimization on the standardized TCM formulae. AI bridges the gap between TCM and modern science and technology. AI may bring clinical TCM diagnostics closer to western medicine. With the help of AI, more scientific evidence about TCM will be discovered. It can be expected that more unified guidelines for specific TCM syndromes will be issued with the development of AI-assisted TCM therapies in the future.

PP369 Development Of A Dysmenorrhea Quality Of Life Scale Based On Traditional Chinese Medicine Theory: A Mixed-Methods Study

IntroductionIt is difficult to generalize health technology assessment in the field of traditional Chinese medicine (TCM). The lack of an outcomes evaluation system based on TCM theory is one of the important reasons. Studies conducted in menstruating women have shown that the prevalence of primary dysmenorrhea varies from 45 to 95 percent. As a debilitating condition for many women, dysmenorrhea is one of the leading causes of absenteeism from school or work, which has a negative effect on quality of life (QoL). TCM has obvious advantages in treating dysmenorrhea. This study aimed to develop a dysmenorrhea QoL scale based on TCM theory.MethodsWe conducted focus group discussions and in-depth interviews with TCM gynecologists and patients, and adapted items from previously published scales. We generated an initial pool of forty-one items with eight domains. The Delphi method was used for preliminary item selection. Then, we administered the items to a sample of adolescent girls (n = 200). The distribution of survey items, discrete trend, factor analysis, correlation coefficient, and Cronbach's α coefficient were used to select items.ResultsAfter two rounds of expert consultation, a total of thirty items were included in the dysmenorrhea QoL scale. And after sample analysis, four items' frequency distribution was skewed, five items' standard deviation (SD) was &lt;0.8, four items' factor loading was &lt;0.4, five items' score correlation coefficient with a related domain was &lt;0.4, and three items’ deletion would cause their domain's Cronbach's α coefficient increased. The items were deleted when they met more than two above standards.ConclusionsA total of twenty items with eight domains were included in the dysmenorrhea QoL scale. The methods to select the dysmenorrhea QoL scale items based on TCM theory were preferable. Given the paucity of research in this area, this new dysmenorrhea QoL scale may provide opportunities for patient-reported outcome evaluation in the field of TCM.

Application and prospects of hyperspectral imaging and deep learning in traditional Chinese medicine in context of AI and industry 4.0

In the 21 st century, the rise of artificial intelligence(AI) marks the arrival of the intelligence era or the era of Industry 4.0. In addition to the rapid development of computer and electronic information science, machine learning, as the core intelligence of AI, provides a new methodology for the modernization of traditional Chinese medicine. The algorithms of machine learning include support vector machine(SVM), extreme learning machine(ELM), convolutional neural network(CNN), and recurrent neural network(RNN). The combination of machine learning algorithms and hyperspectral imaging analysis could be used for the identification of fake and inferior herbs, the origin of herbs and the content determination of bioactive ingredients in herbs, which has largely solved the difficulty in strictly controlling the quality of traditional Chinese medicine. The integration of high spectral imaging(HSI) and deep lear-ning will make the predicted results more reliable and suitable for analysis of great amounts of samples. This paper summarizes the application of hyperspectral imaging technology(HSI) and machine learning algorithms in the field of traditional Chinese medicine in recent years, focuses on the principles of hyperspectral imaging technology, preprocessing methods and deep learning algorithms, and gives the prospects of evolution of hyperspectral imaging technology in the field.

Effect of cupping therapy on the level of pain and neuromuscular variables in women with low back pain

Background: Cupping therapy is a common technique in the field of traditional Chinese medicine, which through sucking on the skinmainly results in pain relief. Objectives: To analyze the effect of cupping therapy on pain intensity, muscle co-contraction and trunkextensor muscle strength in women with low back pain. Methods: 26 women participated, divided into: LBPgroup (n = 13), and controlgroup (n = 13). The level of pain, isometric strength of trunk extensor muscles and co-contraction of superficial and deep trunk muscleswere evaluated. The cupping therapy treatment consisted of 10 sessions, and after the volunteers were reevaluated. Anova RepeatedMeasures were used. Results: There was a 40.1% reduction in pain level, a 13.6% increase in trunk extensor strength, and a decreasein contraction between rectus abdominis and iliocostalis for GDL after treatment. Conclusion: 10 sessions of cupping therapy assistin reducing pain and improving trunk strength in young people with lower back pain.&#x0D;

Visual analysis of knowledge map of network Meta-analysis in traditional Chinese medicine based on CiteSpace

Network Meta-analysis has been widely applied in the field of traditional Chinese medicine(TCM) due to its unique advantages. This study aimed to conduct a visual analysis on the state of the application network Meta-analysis in the field of traditional Chinese medicine. Databases of CNKI and Web of Science were retrieved to identify the qualified literatures and then screen out their titles and abstracts. Institutions, authors, cited references, and keywords were analyzed using the information visualization analysis software CiteSpace. Finally, 79 English and 186 Chinese articles were included. The results indicated that the literatures were mainly published in Chinese, and the number of articles was increased rapidly since 2015. Cooperation between institutions and authors were mainly concentrated inside the institutions. The most important four institutions were four universities who attached more importance to evidence-based medical education and academic exploration. The keywords beside the method of network Meta-analysis could be summarized into three types: the main interventions in traditional Chinese medicine(Chinese herbal injection, herb medicine, acupuncture, etc.), disease types(cancer, circulatory system disease, bone joint disease, urinary system disease, etc.) and the outcome of interests(efficacy, safety, symptom, survive, mortality, etc.), which reflected the current research hotspots to certain extent. In addition, the most cited articles were methodology articles, including the introduction of methodology and the guides of application software, suggesting that the exploration of methodological articles will be extremely concerned.

Identification of curcumin content in raw and vinegar-processed rhizomes of Curcuma kwangsiensis based on electronic nose combined with back propagation neural network

This study aimed to establish a rapid and accurate method for identification of raw and vinegar-processed rhizomes of Curcuma kwangsiensis, in order to predict the content of curcumin compounds for scientific evaluation. A complete set of bionics recognition mode was adopted. The digital odor signal of raw and vinegar-processed rhizomes of Curcuma kwangsiensis were obtained by e-nose, and analyzed by back propagation(BP) neural network algorithm, with the accuracy, the sensitivity and specificity in discriminant model, correlation coefficient as well as the mean square error in regression model as the evaluation indexes. The experimental results showed that the three indexes of the e-nose signal discrimination model established by the neural network algorithm were 100% in training set, correction set and prediction set, which were obviously better than the traditional decision tree, naive bayes, support vector machine, K nearest neighbor and boost classification, and could accurately differentiate the raw and vinegar products. Correlation coefficient and mean square error of the regression model in prediction set were 0.974 8 and 0.117 5 respectively, and could well predict curcumin compounds content in Curcuma kwangsiensis, and demonstrate the superiority of the simulation biometrics model in the analysis of traditional Chinese medicine. By BP neural network algorithm, e-nose odor fingerprint could quickly, conveniently and accurately realize the discrimination and regression, which suggested that more bionics information acquisition and identification patterns could be combined in the field of traditional Chinese medicine, so as to provide ideas and methods for the rapid evaluation and stan-dardization of the quality of traditional Chinese medicine.

Study on establishing a methodology of comprehensive clinical evaluation for Chinese patent medicine based on health technology assessment

At present, most of Chinese patent medicines have problems, such as weak scientific basis, unclear clinical value evaluation, etc., which lead to the lack of sufficient evidence for the entry into the essential medicine list, medical insurance catalog and other important health resource allocation tools. This has a negative impact on the development of traditional Chinese medicine. It is urgent to establish a comprehensive evaluation methodology system of Chinese patent medicine in China. There are at least three reasons including producing evidence for clinical rational use scientifically, developing an objective and transparent selecting strategy, eventuating and highlighting its clinical value. The process and method of health technology assessment(HTA) can provide reference for the establishment of comprehensive evaluation method of Chinese patent medicine. However, HTA is rarely carried out in the field of traditional Chinese medicine. The latest domestic and international research showed that HTA combined with multi-criteria decision analysis(MCDA) can increase the transparency of decision-making and improve the quality of decision-making. The combined two formed the EVIDEM framework, which is conducive to drug selection and its clinical use. In this paper, the EVIDEM framework was introduced to establish the methodology framework of the comprehensive clinical evaluation system of Chinese patent medicine. A preliminary research idea has been put forward. In the future, we can establish a set of comprehensive clinical evaluation methods for Chinese patent medicine in cooperation with relevant national drug decision-making departments and management departments. It is believed that such cooperation could promote the full implementation of the re-evaluation for Chinese patent medicine.

Visual analysis of influenza treated by traditional Chinese medicine based on CiteSpace

To analyze the research status, research hotspots and frontier trends of traditional Chinese medicine (TCM) in the treatment of influenza in the past 20 years through the knowledge graph, so as to provide reference basis for further research. The related literatures of TCM in the treatment of influenza were collected in China National Knowledge Infrastructure (CNKI) from 2000 to 2019. The relevant graphs of authors, research institutions and key words were drawn by CiteSpace 5.6, the distribution and cooperation of main research forces in this field were analyzed, and the research frontiers and hot spot information in this field were discussed. A total of 3 048 related literatures were obtained, involving 949 authors and 242 research institutions. The analysis of the number of articles showed that the volume of articles related to the treatment of influenza with TCM fluctuated greatly in the past 20 years, which was obviously affected by the sudden hot spots around 2010, but showed an overall upward trend, with an average annual volume of about 152 articles. The analysis of the author's cooperation map showed that a total of 77 core authors had published more than 5 articles, accounting for only 8.1% of all authors, and 5 authors had published more than 30 articles. Five major teams had been formed with Gu Ligang, Liu Qingquan, Lu Fangguo, Cui Xiaolan and Zhang Fengxue as the core. The analysis of the cooperation map of research institutions showed that the cooperation among institutions was not good, and only the scientific research institutes in Beijing and Guangzhou had formed a closely related cooperation network. The keyword co-occurrence map showed that 8 keywords appeared more than 100 times, especially ultra-high-frequency keywords, influenza virus ranked first (n = 518). There were 14 key nodes, such as influenza virus, TCM treatment, viral pneumonia and so on, which supported the current research field of TCM in the treatment of influenza. Fourteen clusters were formed to classify the current research hotspots, including the nomenclature of influenza, virus type, TCM treatment, western medicine knowledge, etc., and the map showed that the clustering was reasonable and the structure was significant. Timeline graph showed that parainfluenza virus, virus disease, pharmacodynamics, heat-clearing and detoxifying drugs, bacteriostasis and experimental research had all been studied for more than 8 years, revealing the research hotspots and trends of TCM in the treatment of influenza. The overall research related to the treatment of influenza with TCM is relatively perfect. In the future, the close cooperation among authors and institutions should be strengthened. The molecular mechanism research, clinical and animal trials of TCM should be further studied, so as to improve the research system of TCM treatment of influenza.

Maintaining the predictive abilities of near-infrared spectroscopy models for the determination of multi-parameters in White Paeony Root

Near-infrared spectroscopy (NIRs) has been widely applied in the field of traditional Chinese medicine (TCM). However, the quality of TCM inevitably changes with time and origin, which will result in a decline in the prediction accuracy of constructed NIR models. In this study, models of White Paeony Root were maintained to ensure the accuracy of the predictive values of new samples. The applicability of the original models to the new samples were validated by principal component analysis and model evaluation indexes. Chemometric methods including spectral subtraction correction (SSC) and hierarchical cluster analysis-recalibration (HCA-RC) were introduced to maintain the constructed models. The results demonstrated that, according to the performances of the models, the model maintenance ability of HCA-RC was stronger than that of SSC. With the application of HCA-RC, relative standard error of prediction of moisture, albiflorin and paeoniflorin content were reduced from 5.650%, 29.83% and 39.89% to 2.350%, 14.23% and 14.57%, respectively. This result revealed that HCA-RC could better extract common features from historical and new batches of samples. In addition, the updated HCA-RC models can still be applied for the rapid detection of White Paeony Root. Model maintenance ameliorated the problems of the original models that occurred after a period of application. The updated models contained the characteristics of new batches of samples, which had the potential for long-term continuous application and improved detection efficiency.

Quality evaluation recommendation list and interpretation of traditional Chinese medicine clinical practice guidelines

Based on the idea of establishing a complete guideline evaluation system applicable to the field of traditional Chinese medicine(TCM), the author believes that a complete guideline evaluation system of traditional Chinese medicine clinical practice should be divided into three parts: quality evaluation, clinical applicability evaluation and clinical application investigation. According to the different purposes, different evaluators, different evaluation methods and different evaluation time points in the guideline evaluation, the quality evaluation recommendation list, the clinical applicability evaluation recommendation list and the clinical application questionnaire were formed. Among them, the purpose of quality evaluation is to evaluate the methodological quality in the guideline development process, in order to measure whether the entire guideline development process is scientifically rigorous. The evaluators must be the methodologists with an evidence-based medicine background. Therefore, a logical, detailed and comprehensive guideline quality evaluation list will provide good evaluation tools for the TCM guideline formulation team and play an important role in promoting the quality and application of the guidelines. By referring to the internationally recognized development process and methods of evaluation tools, as well as the proof by authoritative TCM clinical experts and methodologists, the author worked out the quality evaluation list of clinical practice guidelines applicable to the field of TCM by considering the characteristics of TCM field. In this paper, the author introduces the whole list of quality evaluation recommendations, and interprets each item in details, hoping to provide reference for the standardization of TCM clinical practice guidelines in the future.

Transfer learning with deep convolutional neural network for constitution classification with face image

Constitution classification is the basis and core content of constitution research in Traditional Chinese medicine. The convolutional neural networks have successfully established many models for image classification, but it requires a lot of training data. In the field of Traditional Chinese medicine, the available clinical data is very limited. To solve this problem, we propose a method for constitution classification through transfer learning. Firstly, the DenseNet-169 model trained in ImageNet is applied. Secondly, we carefully modify the DenseNet-169 structure according to the constitution characteristics, and then the modified model is trained in the clinical data to obtain the constitution identification network called ConstitutionNet. In order to further improve the accuracy of classification, we integrate the ConstitutionNet with Vgg-16, Inception v3 and DenseNet-121 to test according to the integrated learning idea, and judge the input face image to its constitution type. The experimental results show that transfer learning can achieve better results in small clinical dataset, and the final accuracy of constitution recognition is 66.79%.

Critical quality evaluation and application value of network Meta-analyses in traditional Chinese medicine

To introduce the application status of network Meta-analysis( NMA) in the field of traditional Chinese medicine,and to discuss the application value of NMA in the field of traditional Chinese medicine,this study comprehensively reviewed the systematic reviews with application of NMA in the field of traditional Chinese medicine. CNKI,Wan Fang,Sino Med,VIP,Embase,PubMed and Cochrane Library and the reference list of previous studies were searched. The AMSTAR scale was used to evaluate the quality of literature methodology,and PRISMA-NMA checklist was used to measure the degree of report specification. Overall,122 articles were included,including 80 in Chinese and 42 in English. The included studies centered on cancer,bone and joint disease,cardiovascular disease,respiratory disease,mental disease and digestive disease. Additionally,the intervention can be categorized into three groups,traditional Chinese medicine injection,oral Chinese medicine or prescription,and traditional physical therapy including acupuncture.Nearly one-third of the researches&apos; intervention program is aimed at comparing the effect of Chinese and Western combined therapy and monotherapy. The overall methodology quality grade is medium and the report quality is average,with methodology reporting and result reporting especially need to be improved. The subgroup analysis shows that the methodology quality of the English literatures is evidently higher than Chinese literatures,and the quality of the literatures published after 2015 is higher than those published in or before 2015.This study indicates that the NMA can compare multiple treatments simultaneously,which accords with characteristics of the clinical practice in traditional Chinese medicine that is complex and individual. NMA in the field of traditional Chinese medicine is still in the process of development. With higher level of quality control and reporting as well as the improvement of the statistical methodology and the accumulation of original researches,NMA application in the field of traditional Chinese medicine will be promising.

Applicability analysis and evaluation of aglycones in single-pass intestinal perfusion technique based on PBPK model

Single-pass intestinal perfusion( SPIP) is the common carrier of biopharmaceutics classification system( BCS) to study compound permeability. With the application and deepening study of BCS in the field of traditional Chinese medicine( TCM),SPIP model is becoming more and more common to study the intestinal absorption of TCM ingredients. Based on the limitations of the SPIP model in some researches on TCM permeability,it was speculated in this study that aglycone may be more suitable than the glycoside to study the intestinal absorption problem by using SPIP model. Furthermore,applicability of aglycone components was analyzed and evaluated. In this study,with quercetin,daidzein,formononetin,genistein and glycyrrhetinic acid used as research objects,the quantitative study of SPIP was used to evaluate the intestinal permeability of these aglycones and to predict the effective permeability coefficient( Peff) and absorption fraction( Fa) in human body. By combining studies comparison and analysis on multiple permeability research methods and prediction of human body absorption of aglycones in physiological-based pharmacokinetic models,this paper can further illustrate that the SPIP model is a good tool for studying the permeability of aglycones and predicting human absorption,which can provide data foundation and theoretical reference for researches on SPIP technique and BCS in intestinal absorption of TCM ingredients.

A Comparative Analysis of the Chloroplast Genomes of Four Salvia Medicinal Plants

Abstract Herbgenomics is an emerging field of traditional Chinese medicine (TCM) research and development. By combining TCM research with genomics, herbgenomics can help to establish the scientific validity of TCM and bring it into wider usage within the field of medicine. Salvia Linn. (S. Linn.) is a large genus of Labiatae that includes important medicinal plants. In this herbgenomics study, the complete chloroplast (cp) genomes of two Salvia spp.—namely, S. przewalskii and S. bulleyana, which are used as a surrogate for S. miltiorrhiza—were sequenced and compared with those of two other reported Salvia spp.—namely, S. miltiorrhiza and S. japonica. The genome organization, gene number, type, and repeat sequences were compared. The annotation results showed that both Salvia plants contain 114 unique genes, including 80 protein-coding, 30 transfer RNA (tRNA), and four ribosomal RNA (rRNA) genes. Repeat sequence analysis revealed 21 forward and 22 palindromic sequences in both Salvia cp genomes, and 17 and 21 tandem repeats in S. przewalskii and S. bulleyana, respectively. A synteny comparison of the Salvia spp. cp genomes showed a high degree of sequence similarity in the coding regions and a relatively high divergence of the intergenic spacers. Pairwise alignment and single-nucleotide polymorphism (SNP) analyses found some candidate fragments to identify Salvia spp., such as the intergenic region of the trnV–ndhC, trnQ–rps16, atpI–atpH, psbA–ycf3, ycf1, rpoC2, ndhF, matK, rpoB, rpoA, and accD genes. All of the results—including the repeat sequences and SNP sites, the inverted repeat (IR) region border, and the phylogenetic analysis—showed that S. przewalskii and S. bulleyana are extremely similar from a genetic standpoint. The cp genome sequences of the two Salvia spp. reported here will pave the way for breeding, species identification, phylogenetic evolution, and cp genetic engineering studies of Salvia medicinal plants.

Corrigendum to “Enhancing Clinical Efficacy through the Gut Microbiota: A New Field of Traditional Chinese Medicine” [Engineering 5 (2019) 40–49

Corrigendum to “Enhancing Clinical Efficacy through the Gut Microbiota: A New Field of Traditional Chinese Medicine” [Engineering 5 (2019) 40–49

Comparison of support vector machine, back propagation neural network and extreme learning machine for syndrome element differentiation

Artificial intelligence is a discipline which focuses on the study of simulating and extending human intelligence, while machine learning (ML) is one of the most rapidly developing subfields of AI research. The research of ML in the field of traditional Chinese medicine (TCM), has a bright prospect, as well as a profound significance. To explore the feasibility of using ML methods to approximate the diagnosis of TCM, support vector machine (SVM) is introduced and investigated for syndrome element differentiation of TCM in this paper. Based on 670 medical records, SVM was used to approximate the mapping relations between inputs (set of clinical manifestations) and outputs (set of syndrome elements). The value orders of syndrome elements were adopted to evaluate the approximation results, while attribute partial order structure diagram was employed to discover and visualize the knowledge of the records. Back propagation neural network (BPNN) and extreme learning machine (ELM), as comparative methods, were also employed to deal with the medical data. The value order’s matching results between real and predicted results shows that, for SVM, the matched degree of each record is no less than 65%, while there are at least 88% records whose matched degree is more than 80%; and for BPNN and ELM, the highest proportion of records whose matched degree is more than 80% is only 45%. Using methods of ML to approximate the diagnosis of TCM should be feasible, and more relevant research can be conducted in the future.

Medicinal wild plants used by the Mongol herdsmen in Bairin Area of Inner Mongolia and its comparative study between TMM and TCM

BackgroundEthnobotanical studies on folk medicinal plants used by Mongol herdsmen have been conducted in some areas of Inner Mongolia and Xinjiang, China. However, ethnobotanical findings are preliminary and not comprehensive. Mongolian medicinal botanical knowledge has been gradually decreasing. One of the most important reasons is that Mongolian traditional medicine has become an alternative medicine in pasturing areas of China. Collection and analysis of Mongolian folk medicinal botanical knowledge have become extremely important.MethodsFrom 2008 to 2014, the authors have been to Bairin Right Banner seven times, and from 2016 to 2018, have been to Bairin Left Banner five times. Fieldwork was carried out in 18 villages, and 136 local Mongol herdsmen were interviewed. The methods of free-listing and open-ended questionnaires were used in field survey. Ethnobotanical interview and voucher specimen collections were organized in two ways: local plant specimens were collected beforehand and then interviews were organized; local Mongol herdsmen were invited to the field and were interviewed while collecting voucher specimens. Mongolian was used as the working language, and findings were recorded in Mongolian. Scientific names of plants were confirmed through collection and identification of voucher specimens.ResultsAmong the collected medicinal wild plants, 40 species are used by local Mongol herdsmen. Twenty-six species of folk medicinal plants have been recorded in the literature in the field of Traditional Mongolian Medicine (TMM), and 38 species have been recorded in the field of Traditional Chinese Medicine (TCM). The parts that have medicinal value include roots, whole plant, aerial parts, leaves, fruit, seeds, branches, bulb skin, and stem. For medicinal efficacy, among the collected medicinal plants, 8 species should be fresh. Thirteen species must be dried, and another 16 species can be fresh or dried. After a simple process of sorting and washing, local people soak, pulverize, and mash the medicinal plants. Nineteen species were externally used medicine, and 17 species were internally used medicine (taken orally). Generally, only one or two functions of folk medicine and indications associated with it were provided by local Mongol herdsmen. However, the functions of TMM and TCM and their indications show diversity and have systematic characteristics. More functions of TMM and TCM and their indications have been recorded. In the paper, we also discuss the correspondence between one or two functions of folk medicine with one or two functions of TMM and TCM.ConclusionNot many medicinal wild plant species are used by Mongol herdsmen in the Bairin Area. Fourteen species have not been recorded in the literature of TMM, and 2 species have not been recorded in the literature of TCM. Folk knowledge can provide a certain reference value for searching for new medicinal wild plant species. On the whole, fresh plants are commonly used by Mongol herdsmen in the Bairin Area; boiling is the most common preparation method. Most of the crude materials can be used alone. The externally used medicinal parts are more common than those taken orally. A folk medicinal bath may be regarded as a compound drug mixed with two to five species of plant materials. The local Mongol herdsmen fully understand the function of folk medicines and their indications.