Investigation of Heavy Metal Contents in Traditional Chinese Herbal Medicine Peristrophe roxburghiana Collected from Northwest of Guangxi

Objective] This study was conducted to evaluate the product quality and safety of Peristrophe roxburghiana_ col ected from different places in Hechi City, northwest of Gunagxi, so as to provide basic data for further development and uti-lization of the characteristic plant resource P. roxburghiana. [Method] Contents of 9 kinds of heavy metals including Cd, Mn, Pb, Zn and Cu in the herb were deter-mined by the method of wet digestion-flame atomic absorption spectrophotometry and atomic fluorescence spectrometry, respectively. [Results] Heavy metal contents of Cd, Mn, Pb, Fe, Cu, Zn, As, Hg and Se were 1.62-17.25, 8.93-142.53, 4.37-18.43, 103.7-242.81, 2.55-5.35, 85.40-146.30, 0.07-0.54, 0.00-0.08 and 0.00-0.47 mg/kg, respectively. According to the national food safety standards and Green Trade Standards of lmporting ＆amp; Exporting Medicinal plants ＆amp; Preparations, the heavy metal contents of the P. roxburghiana_samples col ected from different coun-ties in Hechi City exceeded standards or at the critical values. Among which, Cd, Pb and Zn contents of the samples are seriously higher than the standards. [Con-clusion] Therefore, the impact of soil heavy metal pol ution on the safety of edible plants in the northwest of Guangxi should be highly concerned.

Metal ions as effectual tools for cancer with traditional Chinese medicine

Malignant tumor has become a major threat affecting human health,and is one of the main causes of human death.Recent studies have shown that many traditional Chinese medicines(TCM)have good anti-tumor activity,which may improve the therapeutic effect of routine treatment and quality of life with lower toxicity.However,the efficacy of TCM alone for the treatment of tumors is limited.Metal ions are essential substances for maintaining normal physiological activities.This article summarized the multiple mechanisms in which metal ions are involved in the prevention and treatment of tumors in TCM.

The theory development of traditional Chinese medicine constitution: a review

Traditional Chinese medicine constitution (TCMC),as one of the most important parts of Chinese medicine theory,attracted the attention of more and more researchers and many research projects were conducted during past several decades in China's Mainland.This review provided a historic overview of TCMC theory and research progress in its classification,evaluation criteria and epidemiology,so as to give people through a different lens to understand human health.

Detection of consensuses and treatment principles of diabetic nephropathy in traditional Chinese medicine: A new approach

Objective:To propose and test a new approach based on community detection in the field of social computing for uncovering consensuses and treatment principles in traditional Chinese medicine(TCM).Methods:Three Chinese databases(CNKI,VIP,andWan Fang Data)were searched for published articles on TCM treatment of diabetic nephropathy(DN)from their inception until September 31,2014.Zheng classification and herbdatawereextractedfromincluded articlesand usedto construct a Zheng classification and treatment of diabetic nephropathy(DNZCT)network with nodes denoting Zhengs and herbs and edges denoting corresponding treating relationshipsamong them.Community detection was applied to the DNZCT and detected community structures were analyzed.Results:A network of 201 nodes and 743 edges were constructed and six communities were detected.Nodes clustered in the samecommunity captured the samesemantic topic;different communities had unique characteristics,and indicated different treatment principles.Large communities usually represented similar points of view or consensuses on common Zheng diagnoses and herb prescriptions;small communities might help to indicate unusual Zhengs and herbs.Conclusion:The results suggest that the community detection-based approach is useful and feasible for uncovering consensuses and treatment principles of DN treatment in TCM,and could be used to address other similar problems in TCM.

Traditional Chinese Herbal Medicine for Epilepsy Treatment Should Be Administered According to the Seizure Type and Epileptic Syndrome

Traditional Chinese herbal medicine (TCHM) has long been used to treat epilepsy. Although many clinical trials and animal studies have seemingly demonstrated its effect, the question of whether TCHM is efficacious in epileptic patients has not been certified because of insufficient supportive evidence. This insufficient supportive evidence stems from the fact that most of the current studies regarding TCHM for epilepsy treatment are not designed according to the different seizure types and epileptic syndromes (STESs). Here, we explore the reasons why many studies have not considered the various STESs and explain how to treat epilepsy according to the pharmacological mechanism for different STESs and exploit the advantage of TCHM for epilepsy treatment. Then, we explain how we treat epilepsy using TCHM according to the different STESs and Bian Zheng Lun Zi.

Relationship between symptoms of traditional Chinese medicine and indicator of western medicine about liver cirrhosis

Traditional Chinese medicine (TCM) is one of the safe and effective methods to treat liver cir-rhosis. The practitioners of TCM assess hepatic function in term of syndrome. But the course of syndrome differentiation is subjectivity. At pre-sent most of all the researches are focused on the relationship between the syndrome and the Western medicine objective indicators such as child-pugh grade. In fact syndrome is the syn-thesis of signs and symptoms and collecting signs, symptoms is easy than syndrome differ-entiation. We try to explore the relationship be-tween the objective Western medicine standard such as child-pugh grade, decompensation or compensation stage, active or inactive period and the signs and symptoms of TCM by using the data mining method. We use the information gain method to assess the attributes and use five typical classifiers such as logistic, Bayes-Net, NaiveBayes, RBF and C4.5 to obtain the classification accuracy. After attribute selection, we obtain the main symptoms and signs of TCM relating to the stage, period and child-pugh grade about liver cirrhosis. The experiment re-sults show the classification accuracy is im-proved after filtering some symptoms and signs.

Visualization analysis of the international standard ISO/TC 249 for traditional Chinese medicine

Objective This study proposes to visually review the current situation and progress of standards sets by the International Organization for Standardization/Technical Committee on Traditional Chinese Medicine(ISO/TC 249). The review aims to explore the development strategies of the standards, which will exhibit the considerable impact on the economy, trade and exchanges, and cooperation in the area of traditional Chinese medicine(TCM).Methods ISO/TC 249 standards were searched on the ISO website, and their title, proposed time, current stage, scope, and classification were obtained for further summarization. Gephi was utilized to portray the co-occurrence network graph of the ISO/TC 249 standards subject.Results In ISO/TC 249, there were 116 standards, including 81 published standards and 35 developing standards by April 30, 2022. Two withdrawal standards were published after revision, which were not counted in the total standards. The number of published standards has been increasing since the first standard was published in 2014, whose title was “Sterile acupuncture needles for single use”. Among these standards, 17.24%(20/116) standards were in review, 56.03%(65/116) in publication, 3.45%(4/116) in approval, 5.17%(6/116) in enquiry,3.45%(4/116) in committee, and 14.66%(17/116) in preparation, respectively. With 116 standards, most of the research focused on the medicament, as its classification of the International Classification for Standards(ICS) showed the proportion reaching 49.54%. The network analysis data revealed that the top five most frequent words were “materials” “root” “requirements” “products” and “system”, after removing the noise data, such as prepositions,conjunctions, and pronouns. Additionally, the word “system” co-exists with the terms “computerized” “coding” “image” “tongue” and “analysis”;the word “requirement” co-exists with“manufacturing” “decoction” “process” and “materials”;whereas the word “devices” coexists with “pulse” “electric” “skin” and “measurement”.Conclusion With the increased diversification and complexity of problems, the development of standards is also oriented to multidisciplinary fields to cultivate the interdisciplinary talents, and especially the international standardization talents of compound TCM. Multi-angle analysis, formulation, and demonstration of standards, in line with industry needs in different disciplines, enhance the availability of standards and the ability to serve the industry.

Construction and optimization of traditional Chinese medicine constitution prediction models based on deep learning

Objective To cater to the demands for personalized health services from a deep learning per-spective by investigating the characteristics of traditional Chinese medicine(TCM)constitu-tion data and constructing models to explore new prediction methods.Methods Data from students at Chengdu University of Traditional Chinese Medicine were collected and organized according to the 24 solar terms from January 21,2020,to April 6,2022.The data were used to identify nine TCM constitutions,including balanced constitution,Qi deficiency constitution,Yang deficiency constitution,Yin deficiency constitution,phlegm dampness constitution,damp heat constitution,stagnant blood constitution,Qi stagnation constitution,and specific-inherited predisposition constitution.Deep learning algorithms were employed to construct multi-layer perceptron(MLP),long short-term memory(LSTM),and deep belief network(DBN)models for the prediction of TCM constitutions based on the nine constitution types.To optimize these TCM constitution prediction models,this study in-troduced the attention mechanism(AM),grey wolf optimizer(GWO),and particle swarm op-timization(PSO).The models’performance was evaluated before and after optimization us-ing the F1-score,accuracy,precision,and recall.Results The research analyzed a total of 31655 pieces of data.(i)Before optimization,the MLP model achieved more than 90%prediction accuracy for all constitution types except the balanced and Qi deficiency constitutions.The LSTM model's prediction accuracies exceeded 60%,indicating that their potential in TCM constitutional prediction may not have been fully realized due to the absence of pronounced temporal features in the data.Regarding the DBN model,the binary classification analysis showed that,apart from slightly underperforming in predicting the Qi deficiency constitution and damp heat constitution,with accuracies of 65%and 60%,respectively.The DBN model demonstrated considerable discriminative power for other constitution types,achieving prediction accuracy rates and area under the receiver op-erating characteristic(ROC)curve(AUC)values exceeding 70%and 0.78,respectively.This indicates that while the model possesses a certain level of constitutional differentiation abili-ty,it encounters limitations in processing specific constitutional features,leaving room for further improvement in its performance.For multi-class classification problem,the DBN model’s prediction accuracy rate fell short of 50%.(ii)After optimization,the LSTM model,enhanced with the AM,typically achieved a prediction accuracy rate above 75%,with lower performance for the Qi deficiency constitution,stagnant blood constitution,and Qi stagna-tion constitution.The GWO-optimized DBN model for multi-class classification showed an increased prediction accuracy rate of 56%,while the PSO-optimized model had a decreased accuracy rate to 37%.The GWO-PSO-DBN model,optimized with both algorithms,demon-strated an improved prediction accuracy rate of 54%.Conclusion This study constructed MLP,LSTM,and DBN models for predicting TCM consti-tution and improved them based on different optimisation algorithms.The results showed that the MLP model performs well,the LSTM and DBN models were effective in prediction but with certain limitations.This study also provided a new technology reference for the es-tablishment and optimisation strategies of TCM constitution prediction models,and a novel idea for the treatment of non-disease.

基于双阶段元学习的小样本中医舌色域自适应分类方法

舌色是中医(TCM)望诊最关注的诊察特征之一。在实际应用中,通过一台设备采集到的舌象数据训练得到的舌色分类模型应用于另一台设备时,由于舌象数据分布特性不一致,分类性能往往急剧下降。为此,该文提出一种基于双阶段元学习的小样本中医舌色域自适应分类方法。首先,设计了一种双阶段元学习训练策略,从源域有标注样本中提取域不变特征,并利用目标域的少量有标注数据对网络模型进行微调,使得模型可以快速适应目标域的新样本特性,提高舌色分类模型的泛化能力并克服过拟合。接下来,提出了一种渐进高质量伪标签生成方法,利用训练好的模型对目标域的未标注样本进行预测,从中挑选出置信度高的预测结果作为伪标签,逐步生成高质量的伪标签。最后,利用这些高质量的伪标签,结合目标域的有标注数据对模型进行训练,得到舌色分类模型。考虑到伪标签中含有噪声问题,采用了对比正则化函数,可以有效抑制噪声样本在训练过程中产生的负面影响,提升目标域舌色分类准确率。在两个自建中医舌色分类数据集上的实验结果表明,在目标域仅提供20张有标注样本的情况下,舌色分类准确率达到了91.3%,与目标域有监督的分类性能仅差2.05%。

中医药数据资源目录体系构建与研究

目的/意义规范中医药数据资源的有效管理和应用。方法/过程以中医药数据资源为主要研究对象,以目录学为研究方法,参考相关行业领域数据资源分类体系、中医药相关法律法规、中医药领域业务职能和学科分类等资料,提出中医药数据资源目录分类模型及主要内容。结果/结论初步建立中医药数据资源目录分类体系,为中医药数据资源目录数据库构建提供参考。

上海浦东某地脑卒中患者的中医分型特点及治疗情况分析

目的分析上海浦东某地脑卒中患者的中医分型特点及治疗情况,为该地区中医药防治脑卒中提供参考依据。方法收集2020年10月至2021年9月我院中医科的284例脑卒中患者为研究对象。对研究对象脑卒中进行中医辨证诊断,并依据证型给予辨证论治。分析脑卒中患者的中医证型及治疗效果。结果浦东某地男性脑卒中患者多于女性(P<0.05);不同性别患者的年龄比较,差异具有统计学意义(P<0.05);不同性别患者的偏瘫部位比较,差异无统计学意义(P>0.05)。284例患者的中医证型由多到少依次为风痰阻络证、阴虚风动证、气虚血瘀证、痰湿蒙窍证、痰火闭窍证、肝阳暴亢证及痰热腑实证。治疗后,风痰阻络证、阴虚风动证的美国国立卫生院卒中量表(NIHSS)评分低于治疗前(P<0.05);治疗后,风痰阻络证的Barthel指数(BI)评分高于治疗前(P<0.05)。脑卒中患者的治疗总有效率为91.55%。结论浦东某地脑卒中男性患者多于女性,患病年龄小于女性,偏瘫部位与性别无关,中医证型诊断风痰阻络证型最多。现代医学规范化治疗方案结合中医药辨证论治对卒中预后有明显干预作用,中医治疗使用祛风化痰通络之法最多。

背部痧象特征要素数显划分方法

目的通过对痧象图片数据的研究,提出一种数显的客观方法来对背部痧象特征要素进行准确辨识,以避免主观认知不同带来的偏差,帮助人们快速辨识痧象的相关特征,为中医医师的诊断提供一定的客观依据,减少主观化成分。方法首先,采用深度语义分割算法模型对采集的背部痧象图片进行分割,以获取只包含痧象的部分区域,去除图片中其他无关部分,尽可能减少对后续实验所带来的影响。然后针对分割得到的图像,结合中医五脏六腑在背部的映射区,采用关键区域检测的方法对痧象颜色特征进行3种区间的识别;根据中医主观上对于痧象形状的划分,采用像素统计方法将痧象形状划分为片状和点状两种。最后,通过准确度、精确度、召回率、F1值对客观识别的结果进行数据上的评价。结果本文提出的客观数显方法在痧象颜色特征划分上的准确率达到了80.56%,在痧象形状特征的划分上准确率达到了89.60%,能够较为准确地对痧象特征要素进行划分,具有一定的可行性。结论本文提出的数显方法能够对痧象的颜色和形状特征进行较为准确的辨识,可以在很大程度上避免主观认知所造成的辨识不同问题,在辅助医师诊断以及用于中医痧象特征的识别教学方面具有较大的应用前景,可为正确了解痧象特征信息提供帮助。

Consensus on the integrated traditional Chinese and Western medicine criteria of diagnostic classification in polycystic ovary syndrome(draft)

Polycystic ovary syndrome （PCOS） is the most common endocrine and metabolic disorder of women, with complex pathogenesis and heterogeneous manifestations. Professor Jin Yu recently wrote an article entitled ＂Proposal of Diagnosis and Diagnostic Classification of PCOS in Integrated Traditional Chinese and Western Medicine.＂ From this, the Obstetrics and Gynecology branches of the Chinese Association of Integrative Medicine and the China Association of Chinese Medicine collaborated with the Gynecology branch of the Chinese Association for Research and Advancement of Chinese Medicine to draft a report on the consensus of criteria for the diagnosis and classification of PCOS in integrated traditional Chinese and Western medicine. The diagnosis for PCOS includes all three features： （1） oligo-ovulation or anovulation; （2） clinical and/or laboratory evidence of hyperandrogenism; （3） PCOS is classified into four types： types la, Ib, Ila, and lib. Syndrome differentiation types for PCOS in traditional Chinese medicine are as follows： Kidney deficiency with phlegm blockage syndrome, Kidney Yin deficiency with phlegm blockage and blood stasis syndrome, and Kidney deficiency with Liver Qi stagnation syndrome.

A data-driven method for syndrome type identification and classification in traditional Chinese medicine

The efficacy of traditional Chinese medicine （TCM） treatments for Western medicine （WM） diseases relies heavily on the proper classification of patients into TCM syndrome types. The authors developed a data-driven method for solving the classification problem, where syndrome types were identified and quantified based on statistical patterns detected in unlabeled symptom survey data. The new method is a generalization of latent class analysis （LCA）, which has been widely applied in WM research to solve a similar problem, i.e., to identify subtypes of a patient population in the absence of a gold standard. A well-known weakness of LCA is that it makes an unrealistically strong independence assumption. The authors relaxed the assumption by first detecting symptom co-occurrence patterns from survey data and used those statistical patterns instead of the symptoms as features for LCA. This new method consists of six steps： data collection, symptom co-occurrence pattern discovery, statistical pattern interpretation, syndrome identification, syndrome type identification and syndrome type classification. A software package called Lantern has been developed to support the application of the method. The method was illustrated using a data set on vascular mild cognitive impairment.

Bridging the Traditional Chinese Medicine Pattern Classification and Biomedical Disease Diagnosis with Systems Biology

Being the unique core of traditional Chinese medicine （TCM）, pattern classification exerts a direct effect on the efficacy and safety of herbal interventions. In this article, the authors integrated the pattern classification and disease diagnosis with many approaches from systems biology, integration of pattern classification with biomedical diagnosis by systems biology is not only a new direction of personalized medicine development, but also provides a new drug development model. In the further study, the pattern classifications of major diseases will be the focus of research.

中医优势病种临床决策支持系统在“混合痔”中医病历质量控制中的应用

目的:运用中医优势病种临床决策支持系统,提升中医辨证分型的准确性,提升中医病历书写理法方药的一致性,提高中医病历书写质量,提高中医诊疗服务质量。方法:采集2023年3—5月运用中医优势病种临床决策支持系统的混合痔病例163例和2022年3—5月未运用中医优势病种临床决策支持系统的混合痔病例176例,回顾性调查分析两组的方药使用量、中医辨证分型准确性、中药饮片的用药记录、病历书写的理法方药一致性。结果:两组方药使用人次、人均开方次数、人均辨证次数、方药病历记录比较,差异均无统计学意义(P>0.05)。智慧医疗辨证论治组方药内容与病历记录一致性比例[95.45%(147/154)]高于传统医疗辨证论治组[90.36%(150/166)],但差异无统计学意义(P>0.05)。智慧医疗辨证论治组的病历记录中患者病象与疾病证型一致比例[96.75%(149/154)],证型、治则治法、方药三者一致比例[86.14%(143/166)],辨证证型变更比例[56.49%(87/154)]均高于传统医疗辨证论治组的86.14%(143/166)、77.77%(129/166)和7.22%(12/166),差异均有统计学意义(P<0.01或P<0.05)。结论:使用中医优势病种临床决策支持系统有助于规范中医辨证思路,培养中医思维模式,提升病历书写者理法方药的逻辑性,有利于提高中医诊疗服务质量。

中医经典课程主题式教学及考核评价的探索

中医经典课程教学是中医教育的核心,通过将多年伤寒论课程教学的心得体会进行了总结,形成了中医学九年制本博贯通专业学生的伤寒琢课程。其以主题式教学为主要教学模式,在前期的模拟病案教学研究中,凝练了24个教学主题,并且通过课堂提问、组织讨论、查阅文献及心得分享等多种途径,激发学生的学习积极性及主观能动性。针对多维度的教学培养模式,该课程除传统主观题笔试外,又尝试引入学生试批、试诊、试写及试讲等多种考核方式,以此探索构建伤寒琢主题式教学课程的分类评价体系。同时,除中医本博贯通专业学生外,这一教考模式亦可在中医研究生、临床中医师等相关课程中进行阶梯式教学考核的拓展尝试,以此培养其岗位胜任能力。

Classification of interventions in Traditional Chinese Medicine

OBJECTIVE: To describe the key systems used for Traditional Chinese Medicine(TCM) classification.METHODS: The TCM classifications used in the International Classification of Diseases-9 Clinical Modification(ICD-9-CM) volume 3, the ICD-10 Procedure Coding System, the International Classification of Health Interventions, and the Medical Subject Headings(Me SH) and Chinese Traditional Medicine and Materia Medica Subject Headings(TCMe SH) thesauruses were compared regarding descriptive terms, structure, and features of TCM interventions.RESULTS: The National Library of Medicine's Me SH thesaurus is ubiquitous. The ICD-9-CM(volume 3),ICD-10 Procedure Coding System, and International Classification of Health Interventions cover insufficient concepts of TCM, and cannot be used directly as classification systems for TCM interventions. In contrast, the TCM contents of the TCMe SH thesaurus are complete, systematic, and detailed, and its hierarchical structure can be used for effective TCM classification.CONCLUSION: TCM classification is very limited and flawed. The Me SH thesaurus helps decrease the detrimental effect of the language barrier. Similarly, the TCMe SH thesaurus can help those without full command of the Mandarin language to access Chinese literature, but the value of searches using TCMe SH could be improved by collaborative working with Information Specialists who are fluent in Mandarin and understand TCM.

高光谱结合人工神经网络鉴别不同来源的丹参饮片

提出了高光谱结合人工神经网络法(ANN)鉴别不同来源丹参饮片的方法。采集了9种不同来源丹参饮片的高光谱;分别采用最大最小归一化、均值中心化、标准正态变量变换、Savitzky-Golay平滑滤波、多元散射校正等5种光谱预处理方法,结合ANN建立了鉴别这些样品来源的分类模型。测试集验证结果表明,当隐含层节点数设置为17时,对光谱进行均值中心化预处理可建立最佳的ANN模型,分类准确率为98.77%。7种丹参样品判别结果的真正率、命中率和特异度均达到100.00%;其余2种丹参样品的真正率、命中率和特异度也不小于90.00%。

中医药治疗晚期非小细胞肺癌的研究进展

非小细胞肺癌(NSCLC)是一种常见的肺部恶性肿瘤,已成为全球癌症死亡的主要原因之一,晚期NSCLC患者的预后普遍较差,该病已给全球公共卫生带来严重负担。晚期NSCLC的治疗一直是临床面临的难题,由于肿瘤细胞的扩散和转移,局部晚期可能会在新辅助治疗后行手术治疗,但效果往往不尽人意,且副作用较大。近年来,中医药在治疗晚期NSCLC方面取得了显著的进展,受到了广泛关注。该文对近几年中医药治疗晚期NSCLC的相关研究进行归纳总结,探讨了中医药治疗的作用机制,为临床实践提供参考。