Evidence of Cross-Kingdom Gene Regulation by Plant MicroRNAs and Possible Reasons for Inconsistencies.

The debate on whether cross-kingdom gene regulation by orally acquired plant miRNAs is possible has been ongoing for nearly 10 years without a conclusive answer. In this study, we categorized plant miRNAs into different groups, namely, extracellular vesicle (EV)-borne plant miRNAs, extracted plant miRNAs, herbal decoction-borne plant miRNAs, synthetic plant miRNA mimics, and plant tissue/juice-borne plant miRNAs. This categorization aimed to simplify the analysis and address the question more specifically. Our evidence suggests that EV-borne plant miRNAs, extracted plant miRNAs, herbal decoction-borne plant miRNAs, and synthetic plant miRNA mimics consistently facilitate cross-kingdom gene regulation. However, the results regarding the cross-kingdom gene regulation by plant tissue- and juice-borne plant miRNAs are inconclusive. This inconsistency may be due to variations in study methods, a low absorption rate of miRNAs and the selective absorption of plant miRNAs in the gastrointestinal tract. Overall, it is deduced that cross-kingdom gene regulation by orally acquired plant miRNAs can occur under certain circumstances, depending on factors such as the types of plant miRNAs, the delivery mechanism, and their concentrations in the plant.

Application regularity of medicinal and dietary substances for patients during COVID-19 rehabilitation / 数字中医药（英文）

@#Objective This study focused on the application regularity of medicinal and dietary substances (MDS) of traditional Chinese medicine (TCM) diet therapy during rehabilitation, in order to help patients with Corona Virus Disease 2019 (COVID-19) reduce sequelae and improve their life quality. Methods The official websites of the national and provincial health committees, the website of the National Administration of Traditional Chinese Medicine, the China BioMedical Literature Database (CBM), China National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database (VIP), and Wanfang Database were used to search the keywords, such as “coronavirus” “novel coronavirus pneumonia” “COVID-19” “protocol” “guideline” “consensus” and “rehabilitation period”. The search time was from the establishment of databases to July 31, 2022. The prevention and control protocols of various provinces and cities were manually supplemented and screened out. The information on the frequency, property, flavor, meridian tropism, and efficacy of MDS was collected for association rule analysis through the Apriori algorithm. Hierarchical cluster analysis was performed using the Euclidean distance and longest distance. Results A total of 18 protocols were screened out, including 56 lists of TCM diet therapy, and 47 kinds of MDS with a frequency of 132 times during the rehabilitation of COVID-19. Among them, six lists of diet therapy were collected from national websites, 26 from local government websites, and 24 from social and academic institution websites. The intended population can be divided into seven categories including normal recovery, lung-spleen Qi deficiency, deficiency of both Qi and Yin, spleen-stomach weakness, deficiency of Yang Qi, kidney Qi deficiency, and blood deficiency. Shanyao (Dioscoreae Rhizoma) and Lianzi (Nelumbinis Semen), followed by Dazao (Jujubae Fructus) were used most commonly in MDS, with mainly flat property, sweet flavor, and spleen and lung meridians in meridian tropism. Besides, deficiency-tonifying drugs were commonly used in MDS. Through association rule analysis, 12 groups of association MDS pairs were obtained. The pair of Yiyiren (Coicis Semen) and Chenpi (Citri Reticulatae Pericarpium) had the highest Lift value, and Yiyiren (Coicis Semen) was used most frequently in the MDS category for eliminating pathogenic factors. The results of complex network analysis showed that the core MDS were Yiyiren (Coicis Semen), Shanyao (Dioscoreae Rhizoma), Huangqi (Astragali Radix), Fuling (Poria), and Dazao (Jujubae Fructus). Three core categories were classified by cluster analysis, including the category of strengthening spleen, nourishing kidney, and grasping Qi, the category of removing phlegm, abating panting, and regulating Qi, and the category of strengthening the middle-energizer and reinforcing Qi. Conclusion Based on the TCM theory, most patients during the rehabilitation of COVID-19 are in a state of lingering pathogens due to deficient vital Qi. TCM diet therapy is based on the principle of “giving both reinforcing and reducing treatment”, and the MDS combinations focus on both reinforcing the health Qi and eliminating pathogenic factors. The diet therapy mainly uses the MDS with flat property and sweet flavor, which belongs to deficiency-tonifying drugs, adding suitable MDS of pathogen-eliminating drugs according to different situations. The ultimate goal is to promote lung inflammation absorption, improve pulmonary fibrosis, increase immunity, reduce the occurrence of sequelae, and improve life quality.

[Application and progress of data mining in study of compatibility law of traditional Chinese medicine].

Data mining is an important method to obtain the key information from a large amount of data, and it is widely applied in the research on the modernization of traditional Chinese medicine(TCM). The compatibility law of herbs is a key issue in the research of TCM prescriptions. This reflects the flexibility and effectiveness of TCM prescriptions, and it is also a crucial link to the development of TCM modernization. Therefore, it is the core purpose of the research on TCM prescriptions to find the compatibility law of herbs and clarify the scientific connotation. Data mining, as an effective method and an important approach, has formed a standardized system in the research of compatibility law of herbs, which can reveal the relationship between different Chinese herbs and summarize the internal rules in compatibility. Two hundred and twenty two effective papers were sorted out and categorized in this article. The results showed that data mining was mainly applied in finding the core Chinese herb pairs, summarizing the utility and attributes of TCM prescriptions, revealing the relationship between prescriptions, Chinese herbs and syndromes, finding the optimal dose of Chinese herbs, and producing the new prescriptions. The problems of data mining in research of herbs compatibility rules were summarized, and its development and trend in current researches were discussed in this article to provide useful references for the in-depth study of data mining in the compatibility law of Chinese herbs.

Application of an extreme learning machine network with particle swarm optimization in syndrome classification of primary liver cancer.

OBJECTIVE: By optimizing the extreme learning machine network with particle swarm optimization, we established a syndrome classification and prediction model for primary liver cancer (PLC), classified and predicted the syndrome diagnosis of medical record data for PLC and compared and analyzed the prediction results with different algorithms and the clinical diagnosis results. This paper provides modern technical support for clinical diagnosis and treatment, and improves the objectivity, accuracy and rigor of the classification of traditional Chinese medicine (TCM) syndromes. METHODS: From three top-level TCM hospitals in Nanchang, 10,602 electronic medical records from patients with PLC were collected, dating from January 2009 to May 2020. We removed the electronic medical records of 542 cases of syndromes and adopted the cross-validation method in the remaining 10,060 electronic medical records, which were randomly divided into a training set and a test set. Based on fuzzy mathematics theory, we quantified the syndrome-related factors of TCM symptoms and signs, and information from the TCM four diagnostic methods. Next, using an extreme learning machine network with particle swarm optimization, we constructed a neural network syndrome classification and prediction model that used "TCM symptoms + signs + tongue diagnosis information + pulse diagnosis information" as input, and PLC syndrome as output. This approach was used to mine the nonlinear relationship between clinical data in electronic medical records and different syndrome types. The accuracy rate of classification was used to compare this model to other machine learning classification models. RESULTS: The classification accuracy rate of the model developed here was 86.26%. The classification accuracy rates of models using support vector machine and Bayesian networks were 82.79% and 85.84%, respectively. The classification accuracy rates of the models for all syndromes in this paper were between 82.15% and 93.82%. CONCLUSION: Compared with the case of data processed using traditional binary inputs, the experiment shows that the medical record data processed by fuzzy mathematics was more accurate, and closer to clinical findings. In addition, the model developed here was more refined, more accurate, and quicker than other classification models. This model provides reliable diagnosis for clinical treatment of PLC and a method to study of the rules of syndrome differentiation and treatment in TCM.

Systematic Evaluation of Toxicity of Aconite Based on Bibliometric Method.

AIM: Based on the bibliometric method, the toxicity of aconite is analyzed and evaluated. METHODS: Studies on the toxicity of aconite were retrieved from CNKI, CQVIP, Chinese Biomedical Literature Service System, and PubMed, ranging from January 1985 to November 2020. All those studies were formed into the Database of Literature of Toxicity of Aconite (DLTA). Studies on the toxicity of aconite were retrieved from CNKI, CQVIP, SinoMed, and PubMed, respectively. Collecting relevant information in DLTA, we analyzed the hotspots, factors and mechanism of aconite toxicity, and attenuation methods. RESULTS: A total of 445 studies on the toxicity of aconite have been collected. "Compatibility attenuation" and "Processing attenuation" have been the hotspots of aconite toxicity in recent years. Many studies support that the main toxic reactions of aconite are heart damage, liver toxicity, nephrotoxicity, and neurotoxicity. The toxic effect of aconite is related to the effect on the central nervous system. Exciting the vagus nerve reduces the autonomy of the sinus node and damages myocardial cells. The decoction time, dosage, and administration of aconite are the main factors of the toxicity of aconite. There are few studies about the effect of the origin of aconite and the specifications of the medicinal materials on toxicity. Therefore, it is impossible to analyze its relevance. At present, the commonly used methods to reduce the toxicity of aconite mainly include three methods: drug compatibility, processing, and decoction. The most common compatibility with aconite medicines includes licorice, dried ginger, ginseng, and ephedra. Black sliced aconite, steamed slices, and fried slices are less toxic than other processed products. Aconite decoction for more than 60 minutes can basically reach the safe range, and more than 2 hours of decoction may cause the loss of active ingredients. CONCLUSIONS: The research on the mechanisms of aconite dosage-efficacy-toxicity, compatibility, processing, liver toxicity, and nephrotoxicity is still not comprehensive and in-depth. Researchers should perfect toxicity studies of aconite, remove the constraints that affect its clinical application, and promote the clinical use of aconite safely and reasonably.

Key CMM Combinations in Prescriptions for Treating Mastitis and Working Mechanism Analysis Based on Network Pharmacology.

AIMS: Using both data mining and network pharmacology methods, this paper aims to construct a molecule-target-disease network for medicines used for treating mastitis, mine out targets, and signaling pathways related to mastitis and explore the mechanism of Chinese materia medica (CMM) prescriptions in treating mastitis. METHODS: A total of 131 CMM prescriptions for treating mastitis were collected from clinical practice and related literatures. A database of prescriptions for treating mastitis (DPTM) was then constructed. Based on data mining method, Traditional Chinese Medicine Inheritance Support System (TCMISS) was employed to mine out high-frequency CMM and key CMM combinations in DPTM. Subsequently, TCM Systems Pharmacology Database and Analysis Platform (TCMSP) and Traditional Chinese Medicine Information Database (TCM-ID) were searched for the targets of ingredients of high-frequency CMM. Then, Bioinformatics Analysis Tool for Molecular Mechanism of TCM (BATMAN-TCM) was searched for diseases and signaling pathways corresponding to the targets of key CMM combinations. The obtained results were denoted as results 1. In addition, human disease database MalaCards was searched for targets and signaling pathways related to mastitis. The obtained results were denoted as results 2. Results 1 and 2 were compared to obtain targets and signaling pathways included in both results, namely, mastitis-related targets of TCMs and mastitis-related signaling pathways that CMM involves in. Then, the biological functions of these targets and signaling pathways were investigated, on which basis the mechanism of CMM prescriptions in treating mastitis was explored. RESULTS: A total of 12 key TCM combinations were identified. Taraxaci Herba, Glycyrrhizae Radix et Rhizoma, Paeoniae Radix Alba, semen citri reticulatae, etc. were CMM with the highest frequency of use for treating mastitis. The potential targets of these high-frequency CMM in treating mastitis were intercellular adhesion molecule 1 (ICAM-1), interleukin-6 (IL-6), lipopolysaccharide binding protein (LBP), and lactotransferrin. The potential signaling pathways that key CMM combinations may involve in during mastitis treatment were NF-κB signaling pathway, immune system, PI3K/Akt signaling pathway, and TNF signaling pathway. CONCLUSIONS: From a perspective of network pharmacology, molecule-target-disease analysis may serve as an entry point for the research of mechanism of CMM. On this basis, we studied the mechanism of CMM prescriptions in treating mastitis by data mining and comparison of results. Our work thus provides a new idea and method for studying the working mechanism of CMM prescriptions.

A new dibenzofuran and other constituents from Ligularia caloxantha, a Chinese medicinal plant.

A new dibenzofuran named 1,2,4-trimethyl-7,8-dimethoxy-dibenzofuran (1), together with seven known compounds, euparin (2), 2,5-diacetyl-6-hydroxy-benzofuran (3), 2-acetyl-5,6-dimethoxy-benzofuran (4), gummosogenin (5), lupeol (6), stigmasterol (7) and (E)-2,5-dihydroxy-cinnamic acid (8), were isolated from the roots of Ligularia caloxantha, a Chinese medicinal plant. The structures of the compounds were elucidated by spectroscopic methods.

[Research progress in Laggera medicinal plants].

This paper reviewed the worldwide research progresses of the genus Laggera both on phytochemical and pharmacological work in the past few decades. The main secondary metabolites of this genus are proved to be sesquitepenoids, flavonoids and phenolic acids. Phamacological investigations revealed that the certain extracts of some Laggera species possess significant bioactivities on anti-inflammation, anti-tumor and anti-viral infection. This review afforded the comprehensive description of the active components as to provide useful references to elucidate their historical clinical application on upper respiratory infection, influenza, parotitis, and recurrent herpes viral infection.