Exploration of Teaching Reform of TCM Dispensing Technology in Higher Vocational Colleges Based on Traditional Chinese Medicine Skills Competition

This paper aims to thoroughly explore the teaching reform of Traditional Chinese Medicine(TCM)dispensing technology in higher vocational colleges,with a focus on the Traditional Chinese Medicine Skills Competition.By analyzing the current teaching status and main challenges of TCM dispensing technology,and aligning with the requirements of the skills competition,a series of detailed and practical teaching reform measures are proposed.These measures are designed to comprehensively improve the teaching quality of TCM dispensing technology in higher vocational colleges,enhance students’practical skills and professional qualities,and ultimately meet the demand for high-quality,skilled talents in the field of TCM.

Five commonly used traditional Chinese medicine formulas in the treatment of ulcerative colitis:A network meta-analysis

BACKGROUND Currently,traditional Chinese medicine(TCM)formulas are commonly being used as adjunctive therapy for ulcerative colitis in China.Network meta-analysis,a quantitative and comprehensive analytical method,can systematically compare the effects of different adjunctive treatment options for ulcerative colitis,providing scientific evidence for clinical decision-making.AIM To evaluate the clinical efficacy and safety of commonly used TCM for the treatment of ulcerative colitis(UC)in clinical practice through a network metaanalysis.METHODS Clinical randomized controlled trials of these TCM formulas used for the adjuvant treatment of UC were searched from the establishment of the databases to July 1,2022.Studies that met the inclusion criteria were screened and evaluated for literature quality and risk of bias according to the Cochrane 5.1 standard.The methodological quality of the studies was assessed using ReviewManager(RevMan)5.4,and a funnel plot was constructed to test for publication bias.ADDIS 1.16 statistical software was used to perform statistical analysis of the treatment measures and derive the network relationship and ranking diagrams of the various intervention measures.RESULTS A total of 64 randomized controlled trials involving 5456 patients with UC were included in this study.The adjuvant treatment of UC using five TCM formulations was able to improve the clinical outcome of the patients.Adjuvant treatment with Baitouweng decoction(BTWT)showed a significant effect[mean difference=36.22,95%confidence interval(CI):7.63 to 65.76].For the reduction of tumor necrosis factor in patients with UC,adjunctive therapy with BTWT(mean difference=−9.55,95%CI:−17.89 to−1.41),Shenlingbaizhu powder[SLBZS;odds ratio(OR)=0.19,95%CI:0.08 to 0.39],and Shaoyao decoction(OR=−23.02,95%CI:−33.64 to−13.14)was effective.Shaoyao decoction was more effective than BTWT(OR=0.12,95%CI:0.03 to 0.39),SLBZS(OR=0.19,95%CI:0.08 to 0.39),and Xi Lei powder(OR=0.34,95%CI:0.13 to 0.81)in reducing tumor necrosis factor and the recurrence rate of UC.CONCLUSION TCM combined with mesalazine is more effective than mesalazine alone in the treatment of UC.

Knee osteoarthritis:A review of animal models and intervention of traditional Chinese medicine

Background:Knee osteoarthritis(KOA)characterized by degeneration of knee cartilage and subsequent bone hyperplasia is a prevalent joint condition primarily affecting aging adults.The pathophysiology of KOA remains poorly understood,as it involves complex mechanisms that result in the same outcome.Consequently,researchers are interested in studying KOA and require appropriate animal models for basic research.Chinese herbal compounds,which consist of multiple herbs with diverse pharmacological properties,possess characteristics such as multicomponent,multipathway,and multitarget effects.The potential benefits in the treatment of KOA continue to attract attention.Purpose:This study aims to provide a comprehensive overview of the advantages,limitations,and specific considerations in selecting different species and methods for KOA animal models.This will help researchers make informed decisions when choosing an animal model.Methods:Online academic databases(e.g.,PubMed,Google Scholar,Web of Science,and CNKI)were searched using the search terms“knee osteoarthritis,”“animal models,”“traditional Chinese medicine,”and their combinations,primarily including KOA studies published from 2010 to 2023.Results:Based on literature retrieval,this review provides a comprehensive overview of the methods of establishing KOA animal models;introduces the current status of advantages and disadvantages of various animal models,including mice,rats,rabbits,dogs,and sheep/goats;and presents the current status of methods used to establish KOA animal models.Conclusion:This study provides a review of the animal models used in recent KOA research,discusses the common modeling methods,and emphasizes the role of traditional Chinese medicine compounds in the treatment of KOA.

Advances in the treatment of diabetic peripheral neuropathy by modulating gut microbiota with traditional Chinese medicine

Diabetic peripheral neuropathy(DPN)is one of the strongest risk factors for diabetic foot ulcers(neuropathic ulcerations)and the existing ulcers may further deteriorate due to the damage to sensory neurons.Moreover,the resulting numbness in the limbs causes difficulty in discovering these ulcerations in a short time.DPN is associated with gut microbiota dysbiosis.Traditional Chinese medicine(TCM)compounds such as Shenqi Dihuang Decoction,Huangkui Capsules and Qidi Tangshen Granules can reduce the clinical symptoms of diabetic nephropathy by modulating gut microbiota.The current review discusses whether TCM compounds can reduce the risk of DPN by improving gut microbiota.

Exploring the transformative impact of traditional Chinese medicine on depression:Insights from animal models

Depression,a prevalent and complex mental health condition,presents a significant global health burden.Depression is one of the most frequent mental disorders;deaths from it account for 14.3%of people worldwide.In recent years,the integration of complementary and alternative medicine,including traditional Chinese medicine(TCM),has gained attention as a potential avenue for addressing depression.This comprehensive review critically assesses the efficacy of TCM interventions in alleviating depressive symptoms.An in-depth look at different research studies,clinical trials,and meta-analyses is used in this review to look into how TCM practices like herbal formulations,acupuncture,and mindbody practices work.The review looks at the quality of the evidence,the rigor of the methods,and any possible flaws in the current studies.This gives us an idea of where TCM stands right now in terms of treating depression.This comprehensive review aims to assess the efficacy of TCM interventions in alleviating depressive symptoms.In order to learn more about their possible healing effects,the study also looks into how different types of TCM work,such as herbal formulas,acupuncture,and mind-body practices.

Research on the development methodology for clinical practice guidelines for organic integration of traditional Chinese medicine and Western medicine

Integrated traditional Chinese medicine(TCM)and Western medicine(WM)is a new medical science grounded in the knowledge bases of both TCM and WM,which then forms a unique modern medical system in China.Integrated TCM and WM has a long history in China,and has made important achievements in the process of clinical diagnosis and treatment.However,the methodological defects in currently published clinical practice guidelines(CPGs)limit its development.The organic integration of TCM and WM is a deeper integration of TCM and WM.To realize the progression of"integration"to"organic integration",a targeted and standardized guideline development methodology is needed.Therefore,the purpose of this study is to establish a standardized development procedure for clinical practice guidelines for the organic integration of TCM and WM to promote the systematic integration of TCM and WM research results into clinical practice guidelines in order to achieve optimal results as the whole is greater than the sum of the parts.

Systems Theory-Driven Framework for AI Integration into the Holistic Material Basis Research of Traditional Chinese Medicine

This paper introduces a systems theory-driven framework to integration artificial intelligence(AI)into traditional Chinese medicine(TCM)research,enhancing the understanding of TCM’s holistic material basis while adhering to evidence-based principles.Utilizing the System Function Decoding Model(SFDM),the research progresses through define,quantify,infer,and validate phases to systematically explore TCM’s material basis.It employs a dual analytical approach that combines top-down,systems theory-guided perspectives with bottom-up,elements-structure-function methodologies,provides comprehensive insights into TCM’s holistic material basis.Moreover,the research examines AI’s role in quantitative assessment and predictive analysis of TCM’s material components,proposing two specific AIdriven technical applications.This interdisciplinary effort underscores AI’s potential to enhance our understanding of TCM’s holistic material basis and establishes a foundation for future research at the intersection of traditional wisdom and modern technology.

Bio-soft matter derived from traditional Chinese medicine:Characterizations of hierarchical structure,assembly mechanism,and beyond

Structural and functional explorations on bio-soft matter such as micelles,vesicles,nanoparticles,aggregates or polymers derived from traditional Chinese medicine(TCM)has emerged as a new topic in the field of TCM.The discovery of such cross-scaled bio-soft matter may provide a unique perspective for unraveling the new effective material basis of TCM as well as developing innovative medicine and biomaterials.Despite the rapid rise of TCM-derived bio-soft matter,their hierarchical structure and assembly mechanism must be unambiguously probed for a further in-depth understanding of their pharmacological activity.In this review,the current emerged TCM-derived bio-soft matter assembled from either small molecules or macromolecules is introduced,and particularly the unambiguous elucidation of their hierarchical structure and assembly mechanism with combined electron microscopic and spectroscopic techniques is depicted.The pros and cons of each technique are also discussed.The future challenges and perspective of TCM-derived bio-soft matter are outlined,particularly the requirement for their precise in situ structural determination is highlighted.

Integrative analysis of bone-formation associated genes and immune cell infiltration in osteoporosis, and the prediction of active ingredients in targeted traditional Chinese medicine

Objective To explore the differential expression and mechanisms of bone formation-related genes in osteoporosis(OP)leveraging bioinformatics and machine learning methodologies;and to predict the active ingredients of targeted traditional Chinese medicine(TCM)herbs.Methods The Gene Expression Omnibus(GEO)and GeneCards databases were employed to conduct a comprehensive screening of genes and disease-associated loci pertinent to the pathogenesis of OP.The R package was utilized as the analytical tool for the identification of differentially expressed genes.Least absolute shrinkage and selection operator(LASSO)logis-tic regression analysis and support vector machine-recursive feature elimination(SVM-RFE)algorithm were employed in defining the genetic signature specific to OP.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses for the selected pivotal genes were conducted.The cell-type identification by estimating rela-tive subsets of RNA transcripts(CIBERSORT)algorithm was leveraged to examine the infiltra-tion patterns of immune cells;with Spearman’s rank correlation analysis utilized to assess the relationship between the expression levels of the genes and the presence of immune cells.Coremine Medical Database was used to screen out potential TCM herbs for the treatment of OP.Comparative Toxicogenomics Database(CTD)was employed for forecasting the TCM ac-tive ingredients targeting the key genes.AutoDock Vina 1.2.2 and GROMACS 2020 softwares were employed to conclude analysis results;facilitating the exploration of binding affinity and conformational dynamics between the TCM active ingredients and their biological targets.Results Ten genes were identified by intersecting the results from the GEO and GeneCards databases.Through the application of LASSO regression and SVM-RFE algorithm;four piv-otal genes were selected:coat protein(CP);kallikrein 3(KLK3);polymeraseγ(POLG);and transient receptor potential vanilloid 4(TRPV4).GO and KEGG pathway enrichment analy-ses revealed that these trait genes were predominantly engaged in the regulation of defense response activation;maintenance of cellular metal ion balance;and the production of chemokine ligand 5.These genes were notably associated with signaling pathways such as ferroptosis;porphyrin metabolism;and base excision repair.Immune infiltration analysis showed that key genes were highly correlated with immune cells.Macrophage M0;M1;M2;and resting dendritic cell were significantly different between groups;and there were signifi-cant differences between different groups(P<0.05).The interaction counts of resveratrol;curcumin;and quercetin with KLK3 were 7;3;and 2;respectively.It shows that the interac-tions of resveratrol;curcumin;and quercetin with KLK3 were substantial.Molecular docking and molecular dynamics simulations further confirmed the robust binding affinity of these bioactive compounds to the target genes.Conclusion Pivotal genes including CP;KLK3;POLG;and TRPV4;exhibited commendable significant prognostic value;and played a crucial role in the diagnostic assessment of OP.Resveratrol;curcumin;and quercetin;natural compounds found in TCM;showed promise in their potential to effectively modulate the bone-forming gene KLK3.This study provides a sci-entific basis for the interpretation of the pathogenesis of OP and the development of clinical drugs.

Promise and challenges of traditional Chinese medicine,specifically Calculus bovis,in liver cancer treatment

Liver cancer,one of the most common malignancies worldwide,ranks sixth in incidence and third in mortality.Liver cancer treatment options are diverse,inclu-ding surgical resection,liver transplantation,percutaneous ablation,transarterial chemoembolization,radiotherapy,chemotherapy,targeted therapy,immuno-therapy,and traditional Chinese medicine(TCM).A multidisciplinary team(MDT)is essential to customize treatment plans based on tumor staging,liver function,and performance status(PS),ensuring individualized patient care.Treatment decisions require a MDT to tailor strategies based on tumor staging,liver function,and PS,ensuring personalized care.The approval of new first-line and second-line drugs and the establishment of standard treatments based on immune checkpoint inhibitors have significantly expanded treatment options for advanced liver cancer,improving overall prognosis.However,many patients do not respond effectively to these treatments and ultimately succumb to the disease.Modern oncology treatments,while extending patient survival,often come with severe side effects,resistance,and damage to the body,negatively impacting quality of life.Huang et al's study published at World Journal of Gastroenterology rigorously validates the anticancer properties of Calculus bovis,enhancing our understanding of TCM and contributing to new liver cancer treatment strategies.For over 5000 years,TCM has been used in East Asian countries like China to treat various diseases,including liver conditions.Analysis of real-world clinical data suggests that for patients with advanced-stage tumors lacking effective treatments,integrated TCM therapies could provide significant breakthroughs.

Traditional Chinese Medicine Erhuang Suppository for Treatment of Persistent High-risk Human Papillomavirus Infection and Its Impact on Transcriptome of Uterine Cervix

Objective High-risk human papillomavirus(HR-HPV)infection is the chief cause of cervical intraepithelial neoplasia(CIN)and cervical carcinoma.The Erhuang suppository(EHS)is a traditional Chinese medicine(TCM)prepared from realgar(As2S2),Coptidis rhizoma,alumen,and borneolum syntheticum and has been used for antiviral and antitumor purposes.However,whether EHS can efficiently alleviate HR-HPV infection remains unclear.This study was conducted to evaluate the efficacy of EHS for the treatment of persistent HR-HPV infection in the uterine cervix.Methods In this study,we evaluated the therapeutic efficacy of EHS in a randomized controlled clinical trial with a 3-month follow-up.Totally,70 patients with persistent HR-HPV infection were randomly assigned to receive intravaginal administration of EHS or placebo.HPV DNA,ThinPrep cytologic test(TCT),colposcopy,and safety evaluation were carried out after treatment.Microarray analysis was performed to compare transcriptome profiles before and after EHS treatment.A K14-HPV16 mouse model was generated to confirm the efficiency of EHS.Results After 3 months,74.3%(26/35)of the patients in the treatment group were HPV negative,compared to 6.9%(2/29)in the placebo group.High-throughput microarrays revealed distinct transcriptome profiles after treatment.The differentially expressed genes were significantly enriched in complement activation,immune response,and apoptotic processes.The K14-HPV16 mouse model also validated the remarkable efficacy of EHS.Conclusion This study demonstrated that EHS is effective against HR-HPV infection and cervical lesions.Additionally,no obvious systemic toxicity was observed in patients during the trial.The superior efficacy and safety of EHS demonstrated its considerable value as a potential cost-effective drug for the treatment of HPV infection and HPV-related cervical diseases.

Constitution identification model in traditional Chinese medicine based on multiple features

Objective To construct a precise model for identifying traditional Chinese medicine(TCM)constitutions;thereby offering optimized guidance for clinical diagnosis and treatment plan-ning;and ultimately enhancing medical efficiency and treatment outcomes.Methods First;TCM full-body inspection data acquisition equipment was employed to col-lect full-body standing images of healthy people;from which the constitutions were labelled and defined in accordance with the Constitution in Chinese Medicine Questionnaire(CCMQ);and a dataset encompassing labelled constitutions was constructed.Second;heat-suppres-sion valve(HSV)color space and improved local binary patterns(LBP)algorithm were lever-aged for the extraction of features such as facial complexion and body shape.In addition;a dual-branch deep network was employed to collect deep features from the full-body standing images.Last;the random forest(RF)algorithm was utilized to learn the extracted multifea-tures;which were subsequently employed to establish a TCM constitution identification mod-el.Accuracy;precision;and F1 score were the three measures selected to assess the perfor-mance of the model.Results It was found that the accuracy;precision;and F1 score of the proposed model based on multifeatures for identifying TCM constitutions were 0.842;0.868;and 0.790;respectively.In comparison with the identification models that encompass a single feature;either a single facial complexion feature;a body shape feature;or deep features;the accuracy of the model that incorporating all the aforementioned features was elevated by 0.105;0.105;and 0.079;the precision increased by 0.164;0.164;and 0.211;and the F1 score rose by 0.071;0.071;and 0.084;respectively.Conclusion The research findings affirmed the viability of the proposed model;which incor-porated multifeatures;including the facial complexion feature;the body shape feature;and the deep feature.In addition;by employing the proposed model;the objectification and intel-ligence of identifying constitutions in TCM practices could be optimized.

The enlightenment of artificial intelligence large-scale model on the research of intelligent eye diagnosis in traditional Chinese medicine

Eye diagnosis is a method for inspecting systemic diseases and syndromes by observing the eyes.With the development of intelligent diagnosis in traditional Chinese medicine(TCM);artificial intelligence(AI)can improve the accuracy and efficiency of eye diagnosis.However;the research on intelligent eye diagnosis still faces many challenges;including the lack of standardized and precisely labeled data;multi-modal information analysis;and artificial in-telligence models for syndrome differentiation.The widespread application of AI models in medicine provides new insights and opportunities for the research of eye diagnosis intelli-gence.This study elaborates on the three key technologies of AI models in the intelligent ap-plication of TCM eye diagnosis;and explores the implications for the research of eye diagno-sis intelligence.First;a database concerning eye diagnosis was established based on self-su-pervised learning so as to solve the issues related to the lack of standardized and precisely la-beled data.Next;the cross-modal understanding and generation of deep neural network models to address the problem of lacking multi-modal information analysis.Last;the build-ing of data-driven models for eye diagnosis to tackle the issue of the absence of syndrome dif-ferentiation models.In summary;research on intelligent eye diagnosis has great potential to be applied the surge of AI model applications.

Potential of traditional Chinese medicine in the treatment of nonalcoholic fatty liver disease:A promising future

In this editorial,we provide insights into the publication by Niu et al featured in the latest edition of the World Journal of Gastroenterology.Specifically,our focus was on exploring the potential of traditional Chinese medicine(TCM)in treating nonalcoholic fatty liver disease(NAFLD)induced by a high-fat diet through various mechanisms.NAFLD is a common liver condition,affecting approximately 25%of the world's population.It is closely linked to metabolic syndrome,insulin resistance,excessive body weight,and irregular lipid processing,leading to fat accumulation in the liver,as well as oxidative stress and inflammation.While maintaining a healthy diet and active lifestyle are essential for managing NAFLD,treatment options are limited due to undefined pathogenesis and a lack of specific medications.TCM,rooted in traditional Chinese practices,presents a promising alternative through its"syndrome differentiation and treatment"principles,enhancing liver lipid metabolism,reducing inflammation,and addressing fibrosis.Certain herbs,such as Poria cocos,Puaria lobata,and Salvia miltiorrhiza,have shown significant efficacy in reducing fat deposition and improving liver function.Due to systematic research and analysis of mechanisms,TCM is anticipated to yield new approaches to prevent and treat NAFLD,increasing its clinical application.

An interpretability model for syndrome differentiation of HBV-ACLF in traditional Chinese medicine using small-sample imbalanced data

Objective Clinical medical record data associated with hepatitis B-related acute-on-chronic liver failure(HBV-ACLF)generally have small sample sizes and a class imbalance.However,most machine learning models are designed based on balanced data and lack interpretability.This study aimed to propose a traditional Chinese medicine(TCM)diagnostic model for HBV-ACLF based on the TCM syndrome differentiation and treatment theory,which is clinically interpretable and highly accurate.Methods We collected medical records from 261 patients diagnosed with HBV-ACLF,including three syndromes:Yang jaundice(214 cases),Yang-Yin jaundice(41 cases),and Yin jaundice(6 cases).To avoid overfitting of the machine learning model,we excluded the cases of Yin jaundice.After data standardization and cleaning,we obtained 255 relevant medical records of Yang jaundice and Yang-Yin jaundice.To address the class imbalance issue,we employed the oversampling method and five machine learning methods,including logistic regression(LR),support vector machine(SVM),decision tree(DT),random forest(RF),and extreme gradient boosting(XGBoost)to construct the syndrome diagnosis models.This study used precision,F1 score,the area under the receiver operating characteristic(ROC)curve(AUC),and accuracy as model evaluation metrics.The model with the best classification performance was selected to extract the diagnostic rule,and its clinical significance was thoroughly analyzed.Furthermore,we proposed a novel multiple-round stable rule extraction(MRSRE)method to obtain a stable rule set of features that can exhibit the model’s clinical interpretability.Results The precision of the five machine learning models built using oversampled balanced data exceeded 0.90.Among these models,the accuracy of RF classification of syndrome types was 0.92,and the mean F1 scores of the two categories of Yang jaundice and Yang-Yin jaundice were 0.93 and 0.94,respectively.Additionally,the AUC was 0.98.The extraction rules of the RF syndrome differentiation model based on the MRSRE method revealed that the common features of Yang jaundice and Yang-Yin jaundice were wiry pulse,yellowing of the urine,skin,and eyes,normal tongue body,healthy sublingual vessel,nausea,oil loathing,and poor appetite.The main features of Yang jaundice were a red tongue body and thickened sublingual vessels,whereas those of Yang-Yin jaundice were a dark tongue body,pale white tongue body,white tongue coating,lack of strength,slippery pulse,light red tongue body,slimy tongue coating,and abdominal distension.This is aligned with the classifications made by TCM experts based on TCM syndrome differentiation and treatment theory.Conclusion Our model can be utilized for differentiating HBV-ACLF syndromes,which has the potential to be applied to generate other clinically interpretable models with high accuracy on clinical data characterized by small sample sizes and a class imbalance.

Matching traditional Chinese medicine and western medicine-based research:Advanced nutraceutical development for proactive gastric cancer prevention

Gastric cancer(GC),the third leading cause of cancer-related death globally,is complex and heterogeneous.This review explores multidisciplinary investigations of traditional Chinese medicine(TCM)combined with Western medical practices,emphasizing the development of nutraceuticals for cancer prevention.Using advanced analytical chemistry and food chemistry techniques,this study investigated how TCM components may be optimized for nutraceutical development.Focusing on molecular interactions with GC pathways,particularly the NF-κB,PI3K/Akt,and Wnt/β-catenin pathways,we examined the effects of TCM polyherbal formulas,extracts,and isolated compounds.These agents modulate apoptosis and cellular proliferation,underscoring their potential in preventive strategies.The convergence of nutraceutical and medicine food homology studies highlights a significant shift towards integrating TCM-derived compounds in a preventive health framework.This approach aims not only to enhance efficacy and reduce side effects but also to champion a preventive paradigm using personalized medicine to advance proactive health maintenance and disease prevention.The combination of TCM and western medical practices offers promising avenues for future research and practical applications in GC prevention.

Research progress of traditional Chinese medicine in the treatment of endocrine metabolic diseases in 2023

This study aimed to provide a comprehensive review of the research progress in Chinese medicine in the treatment of endocrine metabolic diseases in 2023,covering traditional Chinese medicine(TCM)monomers,TCM extracts,and TCM combinations,including non-alcoholic fatty liver disease,type 2 diabetes mellitus and its complications,obesity,hyperuricaemia,and thyroid disorders.After systematic sorting and summary,we found that in 2023,the research focusing on the application of TCM for endocrine metabolic diseases was still on the mechanism of action at the cellular and molecular levels,which not only influenced the classical pathways of lipid metabolism,but also delved into the key mechanisms of anti-inflammation,anti-oxidation,anti-insulin resistance,and so on.Additionally,TCM has shown remarkable results in the treatment of endocrine metabolic diseases by improving intestinal flora disorders and abnormal cellular iron death.These research results provide valuable ideas,methods,and tools for TCM in the prevention and treatment of endocrine metabolic diseases,and provide important references and guidance for future research and practice.

Integration of traditional,complementary,and alternative medicine with modern biomedicine:the scientization,evidence,and challenges for integration of traditional Chinese medicine

Traditional medicine has garnered significant global recognition,with an estimated 80%of the global population using it.Therefore,it is essential to fully understand the integration of traditional medicines into current healthcare systems.This review aims to provide a comprehensive overview of the standard process to modernize traditional medicine scientifically in the context of modern biomedicine,further termed here as“scientization”.Specifically,we aim to summarize the advancements made in understanding the efficacy,effectiveness,and underlying mechanisms of herbal medicine.We also examined the transition from experience-to evidence-based medicine during acupuncture.Furthermore,we explore the development of universal safety and quality control standards.Finally,we discuss international trade and export markets for Chinese medical products.The development and integration of traditional medicine have allowed it to further improve human health,resulting in a more comprehensive health solution for the global population.

Clinical research report on traditional Chinese patent medicines and traditional Chinese classic famous prescriptions(2022)

Objective:The paper is to comprehensively summarize and analyze the basic situation and methodological quality of clinical randomized controlled trials(RCTs)of traditional Chinese patent medicines and traditional Chinese classic famous prescriptions published in 2022,to provide evidence and reasonable suggestions for the advancement of clinical research and the formulation of policies and guidelines.Methods:The Evidence Database System of clinical evidence-based evaluation of traditional Chinese medicine was searched,and data from China National Knowledge Infrastructure(CNKI),PubMed,and other databases were supplemented.The search duration was from January 1,2022,to December 31,2022.RCTs of traditional Chinese patent medicines and traditional Chinese classic famous prescriptions were included as the source of clinical evidence,and published information,sample size,intervention,control measures,treatment course,methodological quality,and key link report were analyzed and evaluated.Results:A total of 1,464 RCTs of traditional Chinese patent medicines were included,which comprised 667 types of traditional Chinese patent medicines;“traditional Chinese patent medicines+Western medicine vs.Western medicine”was the most widely used intervention and control setting,involving 417 RCTs(28.48%).A total of 245 RCTs of traditional Chinese classic famous prescriptions were included,comprising 55 types of traditional Chinese classic famous prescriptions.“Decoction+conventional treatment vs.conventional treatment”was the most widely used intervention and control setting,with 87 RCTs(35.51%).Published RCTs on traditional Chinese patent medicines and traditional Chinese classic famous prescriptions were limited by the study design and implementation.Most“allocation concealment”and“blinding of patients and personnel”were rated as medium to high risk.There are insufficient reports on key research links such as experimental registration and ethical approval.Conclusions:The number of RCTs on traditional Chinese patent medicines has decreased in 2022,but there has been a slight improvement in the research quality and impact.There are relatively few studies on traditional Chinese classic famous prescriptions.Measures must be taken to improve clinical trial design,implementation,and reporting.Methodological experts should be invited to provide professional technical guidance on the trial design.In the research implementation process,attention should be paid to quality control,particularly the standardization of the randomized execution.

HHO optimized support vector machine classifier for traditional Chinese medicine syndrome differentiation of diabetic retinopathy

AIM:To develop a classifier for traditional Chinese medicine(TCM)syndrome differentiation of diabetic retinopathy(DR),using optimized machine learning algorithms,which can provide the basis for TCM objective and intelligent syndrome differentiation.METHODS:Collated data on real-world DR cases were collected.A variety of machine learning methods were used to construct TCM syndrome classification model,and the best performance was selected as the basic model.Genetic Algorithm(GA)was used for feature selection to obtain the optimal feature combination.Harris Hawk Optimization(HHO)was used for parameter optimization,and a classification model based on feature selection and parameter optimization was constructed.The performance of the model was compared with other optimization algorithms.The models were evaluated with accuracy,precision,recall,and F1 score as indicators.RESULTS:Data on 970 cases that met screening requirements were collected.Support Vector Machine(SVM)was the best basic classification model.The accuracy rate of the model was 82.05%,the precision rate was 82.34%,the recall rate was 81.81%,and the F1 value was 81.76%.After GA screening,the optimal feature combination contained 37 feature values,which was consistent with TCM clinical practice.The model based on optimal combination and SVM(GA_SVM)had an accuracy improvement of 1.92%compared to the basic classifier.SVM model based on HHO and GA optimization(HHO_GA_SVM)had the best performance and convergence speed compared with other optimization algorithms.Compared with the basic classification model,the accuracy was improved by 3.51%.CONCLUSION:HHO and GA optimization can improve the model performance of SVM in TCM syndrome differentiation of DR.It provides a new method and research idea for TCM intelligent assisted syndrome differentiation.