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.

Molecular mechanism and research progress of traditional Chinese medicine in the treatment of prostate cancer

Prostate cancer(PCa)is one of the most common malignant tumors in the male genitourinary system,ranking second in incidence worldwide.Traditional Chinese medicine(TCM),as an important component of complementary and alternative medicine,shows unique advantages in cancer treatment.Chinese herbal medicine is usually composed of multiple ingredients and involves multiple signaling pathways,which showed function of inducing apoptosis of cancer cells,arresting the cell cycle,inhibiting invasion and metastasis,reducing drug resistance,and regulating immune function.Physical therapy is also an important treatment of TCM.Currently,Physical therapy such as acupuncture or Tai Chi and Qigong are gaining increased recognition in the management of PCa,particularly in addressing issues like urinary incontinence and bone metastasis-related pain.This article reviews the TCM treatment and therapy of PCa,in order to provide new research avenues and treatment options for the treatment of PCa with TCM and improve the quality of life of patients.

Traditional Chinese medicine in the treatment of Helicobacter pylorirelated gastritis:The mechanisms of signalling pathway regulations

Helicobacter pylori-associated gastritis(HPAG)is a common condition of the gastrointestinal tract.However,extensive and long-term antibiotic use has resulted in numerous adverse effects,including increased resistance,gastrointestinal dysfunction,and increased recurrence rates.When these concerns develop,traditional Chinese medicine(TCM)may have advantages.TCM is based on the concept of completeness and aims to eliminate pathogens and strengthen the body.It has the potential to prevent this condition while also boosting the rate of Helicobacter pylori eradication.This review elaborates on the mechanism of TCM treatment for HPAG based on cellular signalling pathways,which reflects the flexibility of TCM in treating diseases and the advantages of multi-level,multipathway,and multi-target treatments for HPAG.

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.

Literature study on traditional Chinese medicine syndromes after renal transplantation

BACKGROUND Kidney transplantation is the most effective means to treat patients with renal failure,but its postoperative problems such as rejection reactions,immunosuppressant poisoning,chronic transplant kidney nephropathy,etc.still have not been effectively solved.This study searched for literature on traditional Chinese medicine(TCM)syndromes after kidney transplantation in China,conducted statistical analysis of the results,and sought to identify the underlying patterns.AIM To understand the TCM syndromes after renal transplantation and associated rules and provide a theoretical basis for further clinical research.METHODS The literature pertaining to TCM syndromes in renal transplantation,published in the China National Knowledge Infrastructure,Wanfang database,and WIP database from 1970 to 2021,was meticulously searched and comprehensively and statistically analyzed.RESULTS Following the established inclusion and exclusion criteria,13 studies were selected for analysis.Post-renal transplantation,no significant discrepancy was noted among the groups based on the location of TCM viscera.However,when categorized according to TCM pathogenic factors,the groups with spleen and kidney yang deficiency,as well as liver and kidney yin deficiency,exhibited a statistically significant difference in the frequency.CONCLUSION Currently,the research on TCM syndromes pertaining to renal transplantation is in its nascent phase.It is imperative to conduct a multicentric,large-scale survey of TCM syndromes subsequent to renal transplantation in the ensuing years.

Recognition and quality mapping of traditional herbal drugs:way forward towards artificial intelligence

The use of traditional herbal drugs derived from natural sources is on the rise due to their minimal side effects and numerous health benefits.However,a major limitation is the lack of standardized knowledge for identifying and mapping the quality of these herbal medicines.This article aims to provide practical insights into the application of artificial intelligence for quality-based commercialization of raw herbal drugs.It focuses on feature extraction methods,image processing techniques,and the preparation of herbal images for compatibility with machine learning models.The article discusses commonly used image processing tools such as normalization,slicing,cropping,and augmentation to prepare images for artificial intelligence-based models.It also provides an overview of global herbal image databases and the models employed for herbal plant/drug identification.Readers will gain a comprehensive understanding of the potential application of various machine learning models,including artificial neural networks and convolutional neural networks.The article delves into suitable validation parameters like true positive rates,accuracy,precision,and more for the development of artificial intelligence-based identification and authentication techniques for herbal drugs.This article offers valuable insights and a conclusive platform for the further exploration of artificial intelligence in the field of herbal drugs,paving the way for smarter identification and authentication methods.

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.

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.

Stock Price Prediction and Traditional Models: An Approach to Achieve Short-, Medium- and Long-Term Goals

A comparative analysis of deep learning models and traditional statistical methods for stock price prediction uses data from the Nigerian stock exchange. Historical data, including daily prices and trading volumes, are employed to implement models such as Long Short Term Memory (LSTM) networks, Gated Recurrent Units (GRUs), Autoregressive Integrated Moving Average (ARIMA), and Autoregressive Moving Average (ARMA). These models are assessed over three-time horizons: short-term (1 year), medium-term (2.5 years), and long-term (5 years), with performance measured by Mean Squared Error (MSE) and Mean Absolute Error (MAE). The stability of the time series is tested using the Augmented Dickey-Fuller (ADF) test. Results reveal that deep learning models, particularly LSTM, outperform traditional methods by capturing complex, nonlinear patterns in the data, resulting in more accurate predictions. However, these models require greater computational resources and offer less interpretability than traditional approaches. The findings highlight the potential of deep learning for improving financial forecasting and investment strategies. Future research could incorporate external factors such as social media sentiment and economic indicators, refine model architectures, and explore real-time applications to enhance prediction accuracy and scalability.

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.

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.

Application of multidisciplinary team-based integrated traditional Chinese medicine and Western medicine in rotator cuff injury patients undergoing arthroscopic surgery

BACKGROUND Arthroscopic rotator cuff repair is a common surgical treatment for rotator cuff injuries(RCIs).Although this procedure has certain clinical advantages,it requires rehabilitation management interventions to ensure therapeutic efficacy.AIM To investigate the effect of integrated traditional Chinese medicine and Western medicine(TCM-WM)under the multidisciplinary team(MDT)model on the postoperative recovery of patients undergoing arthroscopic surgery for RCIs.METHODS This study enrolled 100 patients who underwent arthroscopic rotator cuff repair for RCIs at the Seventh People’s Hospital of Shanghai University of Traditional Chinese Medicine between June 2021 and May 2024.They were divided into a control group(n=48)that received routine rehabilitation treatment and an experimental group(n=52)that received TCM-WM under the MDT model(e.g.,acupuncture,TCM traumatology and orthopedics,and rehabilitation).The results of the Constant–Murley Shoulder Score(CMS),Visual Analogue Scale(VAS),Shoulder Pain and Disability Index(SPADI),muscular strength evaluation,and shoulder range of motion(ROM)assessments were analyzed.RESULTS After treatment,the experimental group showed significantly higher CMS scores in terms of pain,functional activity,shoulder joint mobility,and muscular strength than the baseline and those of the control group.The experimental group also exhibited significantly lower VAS and SPADI scores than the baseline and those of the control group.In addition,the experimental group showed significantly enhanced muscular strength(forward flexor and external and internal rotator muscles)and shoulder ROM(forward flexion,abduction,and lateral abduction)after treatment compared with the control group.CONCLUSION TCM-WM under the MDT model improved shoulder joint function,relieved postoperative pain,promoted postoperative functional recovery,and facilitated the recovery of muscular strength and shoulder ROM in patients with RCIs who underwent arthroscopic rotator cuff repair.

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.

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.

Research progress on insomnia treated by traditional Chinese medicine and acupuncture based on microbial-gut-brain axis theory

Insomnia,as one of the emotional diseases,has been increasing in recent years,which has a great impact on people's life and work.Therefore,researchers are eager to find a more perfect treatment.The microbiome-gut-brain axis is a new theory that has gradually become popular abroad in recent years and has a profound impact in the field of insomnia.In recent years,traditional Chinese medicine(TCM)has played an increasingly important role in the treatment of insomnia,especially acupuncture and Chinese herbal medicine.It is the main method of TCM in the treatment of insomnia.This paper mainly reviews the combination degree of"microorganism-gut-brain axis"theory with TCM and acupuncture under the system of TCM.To explore the mechanism of TCM and acupuncture in the treatment of insomnia under the guidance of"microorganismgut-brain axis"theory,in order to provide a new idea for the diagnosis and treatment of insomnia.

Problem identification and revitalization strategies for the recovery and reconstruction of traditional villages in the Ms 6.8 Luding Earthquake

Post-disaster reconstruction is a topic of global concern,and traditional villages have special heritage attributes and need to face more requirements and obstacles in post-disaster reconstruction.This paper summarizes four concepts based on the research on post-disaster reconstruction both domestically and internationally,as well as the recovery and reconstruction of cultural heritage.Through a field survey of traditional villages in the Ms 6.8 Luding earthquake-stricken area,it is found that there are problems such as insufficient awareness of heritage value,misalignment of scientific reconstruction technology,and insufficient protection of reconstruction elements during the reconstruction process.Traditional villages face the risk of declining or even loss of heritage value.In order to effectively protect traditional villages and inherit the carrier of regional culture,four targeted reconstruction response strategies are proposed,i.e.,to"establish special planning for traditional village preservation","emphasize recovery of the authenticity of village heritage","ensure elements for village heritage recovery"and"promote the activation and utilization of village heritage",based on the problems discovered during the survey and the four concepts summarized in the research on post-disaster reconstruction of traditional villages.The research results hope to provide useful reference for ancient cultural areas affected by earthquakes on how to protect cultural heritage during the post-disaster reconstruction process.

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.

Feasibility and simulation model of a pilot scale membrane bioreactor for wastewater treatment and reuse from Chinese traditional medicine

The lack and pollution of water resource make wastewater reuse necessary. The pilot scale long-term tests for submerged membrane bioreactor were conducted to treat the effluents of anaerobic or aerobic treatment process for the high-strength Chinese traditional medicine wastewater. This article was focused on the feasibility of the wastewater treatment and reuse at shorter hydraulic retention time （HRT） of 5.0, 3.2 and 2.13 h. MLSS growth, membrane flux, vacuum values and chemical cleaning periods were also investigated. The experimental results of treating two-phase anaerobic treatment effluent demonstrated that the CODfilt was less than 100 mg/L when the influent COD was between 500-10000 mg/L at HRT of 5.0 h, which could satisfy the normal discharged standard in China. The experimental results to treat cross flow aerobic reactor effluent demonstrated that the average value of CODfilt was 17.28 mg/L when the average value of influent COD was 192.84 mg/L at HRT of 2.13 h during 106 d, which could completely meet the normal standard for water reuse. The maximum MLSS and MLVSS reached 24000 and 14500 mg/L at HRT of 3.2 h respectively. Membrane flux had maximal resume degrees of 94.7% at vacuum value of 0.02 MPa after cleaning. Chemical cleaning periods of membrane module were 150 d. A simulation model of operational parameters was also established based on the theory of back propagation neural network and linear regression of traditional mathematical model. The simulation model showed that the optimum operational parameters were suggested as follows： HRT was 5.0 h, SRT was 100 d, the range of COD loading rate was between 10.664-20.451 kg/（m3.d）, the range of MLSS was between 7543-13694 mg/L.

Classic mechanisms and experimental models for the anti-inflammatory effect of traditional Chinese medicine

Inflammation is a common disease involved in the pathogenesis,complications,and sequelae of a large number of related diseases,and therefore considerable research has been directed toward developing anti-inflammatory drugs for the prevention and treatment of these diseases.Traditional Chinese medicine(TCM)has been used to treat inflammatory and related diseases since ancient times.According to the re-view of abundant modern scientific researches,it is suggested that TCM exhibit anti-inflammatory effects at different levels,and via multiple pathways with various targets,and recently a series of in vitro and in vivo anti-inflammatory models have been developed for anti-inflammation research in TCM.Currently,the reported classic mechanisms of TCM and experimental models of its anti-inflammatory effects pro-vide reference points and guidance for further research and development of TCM.Importantly,the research clearly confirms that TCM is now and will continue to be an effective form of treatment for many types of inflammation and inflammation-related diseases.

Impacts of agri-food e-commerce on traditional wholesale industry:Evidence from China

Rapidly expanding studies investigate the effects of e-commerce on company operations in the retail market.However,the interaction between agri-food e-commerce(AEC)and the traditional agri-food wholesale industry(AWI)has not received enough attention in the existing literature.Based on the provincial panel data from 2013 to 2020 in China,this paper examines the effect of AEC on AWI,comprising three dimensions:digitalization(DIGITAL),agrifood e-commerce infrastructure and supporting services(AECI),and agri-food e-commerce economy(AECE).First,AWI and AEC are measured using an entropy-based combination of indicators.The results indicate that for China as a whole,AWI has remained practically unchanged,whereas AEC exhibits a significant rising trend.Second,the findings of the fixed-effect regression reveal that DIGITAL and AECE tend to raise AWI,whereas AECI negatively affects AWI.Third,threshold regression results indicate that AECI tends to diminish AWI with three-stage inhibitory intensity,which manifests as a first increase and then a drop in the inhibition degree.These results suggest that with the introduction of e-commerce for agricultural product circulation,digital development will have catfish effects that tend to stimulate the vitality of the conventional wholesale industry and promote technical progress.Furthermore,the traditional wholesale industry benefits financially from e-commerce even while it diverts part of the traditional wholesale circulation for agricultural products.