Application of Animal Models of Corneal Neovascularization Based on Data Mining / 中国实验方剂学杂志

ObjectiveTo provide a reference for the establishment of an ideal corneal neovascularization （CNV） animal model by summarizing the modeling characteristics of CNV animal models. MethodWith "CVN" as the theme word， this paper searched the China National Knowledge Infrastructure （CNKI）， Wanfang， Chinese medical journals full-text database， and PubMed database and screened out relevant literature on CNV animal experiments from 2013 to 2023. The database was established by Excel 2021， and the experimental animal strain， gender， modeling method， detection index， and application category were sorted out. The characteristics of the CNV animal model were analyzed. ResultAfter comparative analysis， it was found that the animal strains were Sprague-Dawley rats （87 times， 29.49%） and New Zealand white rabbits （52 times， 17.63%）. Male animals were recommended. Most modeling methods for efficacy verification and mechanism studies were the alkali burn method. Index detection methods included apparent index observation， histopathological detection， immunohistochemistry （IHC）， Western blot， and various polymerase chain reaction （PCR） tests. Detection indexes included apparent indication， corneal histopathology， CNV regulation， etc. ConclusionThe CNV model of SD rats induced by the alkali burn method is recommended for model replication， and the indexes are mainly selected from the growth of CNV， corneal histopathological test， and vascular endothelial growth factor （VEGF）-related test. In addition， according to the demand， the corneal apparent indication and the basic indexes related to the regulation of CNV， such as vascular endothelial growth factor receptor 2 （VEGFR2）， basic fibroblast growth factor （bFGF）， and secretogranin Ⅲ （Scg3） are also selected. Clinical treatment of CNV relies on anti-inflammatory drugs and anti-VEGF drugs， and there is a lack of application of traditional Chinese medicine （TCM）， so the model needs to be improved by adding elements of TCM syndromes.

Mining and analysis of acalabrutinib-induced ADE risk signals based on FDA adverse event reporting system / 中国药房

OBJECTIVE To provide reference for the clinically safe application of acalabrutinib by mining and analyzing the risk signals of adverse drug events （ADE）. METHODS The acalabrutinib-induced ADE reports were extracted from the U.S. FDA adverse event reporting system using the OpenVigil 2.1 platform from November 1， 2017 to March 31， 2023. The reporting odds ratio （ROR） method and composite criteria method from the Medicines and Healthcare Products Regulatory Agency （MHRA） were used for detection of ADE signals. RESULTS There were 7 869 ADE reports of acalabrutinib as the primary suspect drug and 142 ADE positive signals were detected from them， involving 20 system organ classes， which was generally consistent with the ADE recorded in the drug instruction of acalabrutinib， mainly involving general disorders and administration site conditions， various inspection， blood and lymphatic system disorders， various neurological disorders and cardiac disorders. In addition， this study identified several new potential ADE signals that were not mentioned in the drug instruction， including sudden cardiac death， pulmonary toxicity， tumor lysis syndrome， pleural effusion， dyspepsia， gastroesophageal reflux disease， bone pain， decreased blood pressure， and abnormal blood sodium， etc. CONCLUSIONS When using acalabrutinib， in addition to paying attention to the ADE recorded in its instructions， the risk of serious ADE that may lead to death， such as sudden cardiac death and pulmonary toxicity， should also be evaluated to avoid or reduce the occurrence of ADE as much as possible.

Application of data mining algorithms in research on traditional Chinese medicine formula / 中国药房

In recent years， data mining algorithms have been widely employed in scientific research within the field of traditional Chinese medicine （TCM）. The data mining algorithms are used to effectively handle and analyze the complex data in TCM formulas， providing a rational explanation for the mechanism of action. This method has proven particularly useful in uncovering patterns of compatibility and frequent combinations of herbs in TCM， thereby enhancing the reliability and accuracy of clinical diagnosis， target screening， and the study of new drugs. This paper reviews and analyzes 147 papers on TCM formula research that utilize data mining algorithms. The results indicate that data mining algorithms play a unique advantage in six sub- areas， including the study on the mechanism of action in TCM formula， the dose-efficacy of TCM formulas， the identification of core drugs pairs/groups， mining the relationships among “formulas-drug-symptom”， the discovery of new formulas， and mining the compatibility law. Notably， association rules and clustering algorithms are the most representative.

Clinical Manifestations of Wegener Granulomatosis in Iranian Ethnicities Using the K-Means Algorithm: A Descriptive Study

Abstract Introduction Wegener granulomatosis (WG) appears with clinical symptoms, including recurrent respiratory infection, renal manifestations, and nonspecific systemic symptoms. Objective To study the clinical manifestations of WG in Iranian ethnicities, and data on 164 patients were recorded from 2013 to 2018. Methods The data included demographics, symptoms, and the Birmingham Vasculitis Activity Score (BVAS). The symptoms involved the following sites: the nose, sinus, glottis, ears, lungs, kidneys, eyes, central nervous system, mucous membranes, skin, heart, stomach, intestine, as well as general symptoms. The clinical manifestations of nine ethnicities were analyzed. Results In total, 48% of the patients were male and 51% were female, with a median age of 51 years. The BVAS was of 15.4, the sites most involved were the sinus (n =155), nose (n = 126), lungs (n = 125), and ears (n =107). Gastrointestinal (n = 14) and cardiac (n = 7) involvement were less common. Among the patients, 48.17% were Persian, 13.41% were Azari, 11.17% were Gilaki, 11.17% were Kurd, and 10.9% were Lor. Conclusion Our findings indicated that the sinus, nose, lungs, and ears were the sites most involved, and gastrointestinal and cardiac involvement were less common. In the present study, involvement of the upper and lower respiratory tract was higher than that reported in Western and Asian case series. Moreover, we report for the first time that, in all patients with ear involvement, the left ear was the first to be affected. The clinical manifestations among Iranian ethnicities were not different, and the Gilaki ethnicity had the highest BVAS, mostly because the weather was humid; therefore, in Iran, in areas with humidity, the rate of the disease was higher.

Análisis de interacciones de los actores de la red de conocimiento en salud ambiental del Observatorio Nacional de Salud de Colombia

Introducción: Las interrelaciones positivas y negativas entre el hombre y el medioambiente impactan en la salud general de la población, por esto, la gestión del conocimiento y la transformación social, orientadas a la prevención de la exposición a factores de riesgo ambiental y a la creación de ambientes propicios, deben realizarse a través de acciones multidisciplinares intersectoriales, como el trabajo colaborativo de redes del conocimiento. Objetivo: Describir las interacciones entre los actores de la Red de Conocimiento de Salud Ambiental del Observatorio Nacional de Salud de Colombia (ONS), con el fin de promover, mejorar y fortalecer la colaboración, intercambio de información y planificación conjunta de acciones. Metodología: Estudio descriptivo transversal de análisis de redes sociales mediante herramientas de minería de texto del lenguaje de programación R. Se analizaron las categorías de agua y saneamiento, clima, calidad del aire, radiaciones electromagnéticas e intoxicaciones químicas de un corpus documental de 99 textos de los actores de la red general de conocimiento en salud pública del ONS. Se calcularon medidas de centralidad y prestigio y se graficaron redes dirigidas multicapa con Power BI. Resultados: Los actores con mayor centralidad en la red fueron: Ministerio de Salud y Protección Social, Superintendencia de Salud, Profamilia, universidades de Antioquia y La Salle, ONS, Observatorio de Salud Ambiental de Bogotá, Organización Panamericana de la Salud y Organización Mundial de la Salud. Las cinco categorías analizadas presentaron bajas centralidades de grado, y las categorías de agua y clima mostraron mayor participación de los actores (más nodos e interacciones). Conclusiones: El análisis de redes sociales permitió identificar temas relevantes de salud ambiental entre los actores de la red del ONS, además de actores clave para desarrollar espacios de interacción y gestión del conocimiento. Acorde con las limitaciones del análisis, se sugiere la inclusión de aproximaciones bibliométricas para la actualización de las interacciones de la red.

Introduction: Positive and negative interactions between the human beings and the environment have an impact on the general health of the population. Therefore, it is necessary to use knowledge management and social transformation, in order to limit exposure to environmental risk factors by creating a favorable environment for healthcare. This should be carried out through multidisciplinary and intersectorial actions, such as the collaborative work of knowledge networks. Objective: To describe the interactions between the actors within the Environmental Health Knowledge Network Colombia's National Observatory of Health (ONS acronym in Spanish), in order to promote, improve and strengthen collaboration, information exchange and planning of collaborative actions. Methodology: Cross-sectional descriptive study to analyze social interactions through text mining tools by R, programmer language. Categories analyzed: Water and sanitation, climate, air quality, electromagnetic radiation and chemical poisoning. Data source: a documentary corpus of 99 texts done by actors of Environmental Health Knowledge Network of Colombia's ONS. We calculated centrality and prestige measures. We used Power BI in order to plot multi-layered directed networks. Results: Actors with greatest centrality in the network: Ministry of Health and Social Protection, Health Superintendency, Profamilia, Antioquia and La Salle universities, National Health Observatory, Bogota's Observatory of Environmental Health, the Pan American Health Organization and the World Health Organization. The five categories analyzed provides a low centrality degree, and water and climate categories presented greater participation by actors (more nodes and links). Conclusions: Social interactions analysis provides the identification of relevant environmental health issues in Colombia and key actors in order to develop interaction spaces for knowledge management. The analysis had limitations that suggest the inclusion of bibliometric approaches for updating the interactions within the network.

Modelo predictivo de enfermedad cardiovascular basado en inteligencia artificial en la atención primaria de salud / A Predictive Model for Cardiovascular Disease based on Artificial Intelligence in Primary Health Care

Introducción: En Cuba y en el resto del mundo, las enfermedades cardiovasculares son reconocidas como un problema de salud pública mayúsculo y creciente, que provoca una alta mortalidad. Objetivo: Diseñar un modelo predictivo para estimar el riesgo de enfermedad cardiovascular basado en técnicas de inteligencia artificial. Métodos: La fuente de datos fue una cohorte prospectiva que incluyó 1633 pacientes, seguidos durante 10 años, fue utilizada la herramienta de minería de datos Weka, se emplearon técnicas de selección de atributos para obtener un subconjunto más reducido de variables significativas, para generar los modelos fueron aplicados: el algoritmo de reglas JRip y el meta algoritmo Attribute Selected Classifier, usando como clasificadores el J48 y el Multilayer Perceptron. Se compararon los modelos obtenidos y se aplicaron las métricas más usadas para clases desbalanceadas. Resultados: El atributo más significativo fue el antecedente de hipertensión arterial, seguido por el colesterol de lipoproteínas de alta densidad y de baja densidad, la proteína c reactiva de alta sensibilidad y la tensión arterial sistólica, de estos atributos se derivaron todas las reglas de predicción, los algoritmos fueron efectivos para generar el modelo, el mejor desempeño fue con el Multilayer Perceptron, con una tasa de verdaderos positivos del 95,2 por ciento un área bajo la curva ROC de 0,987 en la validación cruzada. Conclusiones: Fue diseñado un modelo predictivo mediante técnicas de inteligencia artificial, lo que constituye un valioso recurso orientado a la prevención de las enfermedades cardiovasculares en la atención primaria de salud(AU)

Introduction: In Cuba and in the rest of the world, cardiovascular diseases are recognized as a major and growing public health problem, which causes high mortality. Objective: To design a predictive model to estimate the risk of cardiovascular disease based on artificial intelligence techniques. Methods: The data source was a prospective cohort including 1633 patients, followed for 10 years. The data mining tool Weka was used and attribute selection techniques were employed to obtain a smaller subset of significant variables. To generate the models, the rule algorithm JRip and the meta-algorithm Attribute Selected Classifier were applied, using J48 and Multilayer Perceptron as classifiers. The obtained models were compared and the most used metrics for unbalanced classes were applied. Results: The most significant attribute was history of arterial hypertension, followed by high and low density lipoprotein cholesterol, high sensitivity c-reactive protein and systolic blood pressure; all the prediction rules were derived from these attributes. The algorithms were effective to generate the model. The best performance was obtained using the Multilayer Perceptron, with a true positive rate of 95.2percent and an area under the ROC curve of 0.987 in the cross validation. Conclusions: A predictive model was designed using artificial intelligence techniques; it is a valuable resource oriented to the prevention of cardiovascular diseases in primary health care(AU)

Forecasting The Risk Of Chronic Kidney Disease Using Artificial Intelligence Approaches

In this Paper With the aid of AI techniques, this study aims to predict the early detection of chronic kidney disease, also known as chronic renal disease, in diabetic patients. It then suggests a decision tree to reach specific conclusions with desired accuracy by evaluating its performance in relation to its specification and sensitivity. Methods: The behaviour of learning algorithms based on a set of data mining indicators affects the models that are produced proportionately. Predicting the future is no longer a difficult task thanks to the promises of predictive analytics in big data and the use of machine learning algorithms, especially for the health sector, which has undergone significant evolution as a result of the development of new computer technologies that gave rise to numerous fields of study research. Many initiatives are made to deal with the explosion of medical data on the one hand, and to learn meaningful information from it, forecast diseases, and anticipate treatments on the other. To extract meaningful information and aid in decision-making, researchers used all the technological advancements, including big data analytics, predictive analytics, machine learning, and learning algorithms.

Application of data mining to extract knowledge about the occurrence of fistulas after palatoplasty / Aplicação de mineração de dados para extração de conhecimento sobre ocorrência de fístulas após palatoplastia

Introduction: Data mining techniques expand access to important information for the decision-making process during health care. The objective the study proposes using data mining techniques to identify variables (surgical treatment protocols, patient characteristics, post-surgical complications) associated with fistulas after primary palatoplasty in patients with unilateral transforamen incisor cleft (UTIC). Method: A data set of 222 patients with UTIC without syndromes, operated by four surgeons with Furlow's or von Langenbeck's primary palatoplasty techniques, was analyzed for this study. Two models for detecting the outcome of surgery were induced using data mining techniques (Decision Tree and Apriori). Results: Five rules were selected from a decision tree pointing to some variables as predictors of fistulas associated with primary palatoplasty: infection, cough, hypernasality, and surgeon. Analysis of the model indicates that it correctly classifies 95.9% of occurrences between the absence and presence of fistulas. The second model indicates that the absence of post-surgical complications (infection and fever) and normal speech results (absent hypernasality, without suggestive of velopharyngeal dysfunction) are related to the absence of fistulas. Regarding surgical procedures, the Furlow technique and the Vomer flap were more frequent in patients with fistulas. Conclusion: Data mining techniques, as applied in the present study, pointed to infection and cough, hypernasality, and surgeon and surgical techniques as predictors of fistulas related to primary palatoplasty.

Introdução: As técnicas de mineração de dados ampliam o acesso a informações importantes para o processo de tomada de decisão durante os cuidados com a saúde. O objetivo do estudo propõe a utilização de técnicas de mineração de dados para identificar variáveis (protocolos de tratamento cirúrgico, características do paciente, intercorrências pós-cirúrgicas) associadas à ocorrência de fístulas após palatoplastia primária em pacientes com fissura transforame incisivo unilateral (FTIU). Método: Um conjunto de dados de 222 pacientes com FTIU sem síndromes, operados por quatro cirurgiões com as técnicas de palatoplastia primária de Furlow ou von Langenbeck, foi analisado para este estudo. Dois modelos para detecção do resultado da cirurgia foram induzidos usando técnicas de mineração de dados (Árvore de Decisão e Apriori). Resultados: Cinco regras foram selecionadas de uma árvore de decisão apontando para algumas variáveis como preditivas de fístulas associadas à palatoplastia primária: infecção, tosse, hipernasalidade, cirurgião. A análise do modelo indica que ele classifica corretamente 95,9% das ocorrências entre ausência e presença de fístulas. O segundo modelo indica que a ausência de intercorrências pós-cirúrgicas (infecção e febre) e resultado de fala normal (hipernasalidade ausente, sem sugestivo de disfunção velofaríngea) estão relacionados à ausência de fístulas. Em relação aos procedimentos cirúrgicos, o uso da técnica de Furlow e retalho de Vomer foram mais frequentes nos pacientes com fístulas. Conclusão: Técnicas de mineração de dados, conforme aplicadas no presente estudo, apontaram para infecção e tosse, presença de hipernasalidade, cirurgião e técnica cirúrgica como preditores de fístulas relacionadas à palatoplastia primária.

Association rules between hair selenium level and residents' diet in Keshan disease area of Zhangjiakou in 2018 -2020 / 公共卫生与预防医学

Objective To explore the related factors of hair selenium level in Keshan disease area of Zhangjiakou City, Hebei Province, and to provide reliable data basis for consolidating the elimination of Keshan disease. Methods The association rule (Apriori) analysis was carried out on the survey data of hair selenium level of people in Keshan disease endemic areas and non-endemic areas of Zhangjiakou City from 2018 to 2020. By setting the minimum support and confidence, and combining with the lift ratio, the association relationship between the hair selenium level of people in Keshan disease area and the staple food and vegetables of the residents was analyzed. Results A total of 5 strong association rules were generated. The maximum values of support, confidence and lift ratio were 12.22, 93.33 and 1.17, respectively, and the minimum values were 10.00, 90.91 and 1.14, respectively. The moderate level of selenium in the hair of residents in the disease area was related to the consumption of food purchased from other places and a large quantity of vegetables. Conclusion Association rules provide a reference research method for improving hair selenium nutrition level of residents in Keshan disease area of Zhangjiakou City and establishing a long-term mechanism for Keshan disease prevention and control.

Mining and analysis of adverse drug reaction signals of melphalan based on FAERS / 中国药房

OBJECTIVE To mine the adverse drug reaction （ADR） signals of melphalan， so as to provide reference for clinically safe drug use. METHODS Using OpenVigil 2.1 data platform， relative ADR reports of melphalan from the first quarter of 2004 to the second quarter of 2022 in FAERS database were collected； data mining was conducted using the reported odds ratio （ROR） method and Medicines and Healthcare Products Regulatory Agency （MHRA） method of disproportional method. ADR reports were described and classified according to the system organ class （SOC） and preferred term （PT） in Medical Dictionary for Regulatory Activities （24.0 edition）. RESULTS A total of 17 046 ADR reports related to the target drug melphalan were retrieved， and the number of ADR reports showed a fluctuating upward trend； the majority of patients were male （43.28%）， and were concentrated between the ages of 50-＜75 （35.09%）， with the main reporting country being the United States （23.97%）； ADR report involved a total of 22 842 severe outcomes， mainly including hospitalization or extended hospitalization （24.45%）. Totally 403 ADR signals were detected， involving 23 SOC， mainly including blood and lymphatic system diseases （801 cases， 13.77%）， followed by eye organ diseases （755 cases， 12.97%） and infectious and invasive diseases （716 cases， 12.30%）. The ADR signals ranked high in the number of reported cases included febrile neutropenia， diarrhea， fever and mucositis and other PT； PT such as pneumonia， sepsis， vitreous hemorrhage， chorioretinal atrophy， myelodysplastic syndrome were not recorded in drug instructions. The ADR signals with high signal strength ranking included choroidal dystrophy， chorioretinal atrophy， eyeball atrophy and other PT， and above three types of PT were not included in the drug instructions. CONCLUSIONS ADRs caused by melphalan mainly include blood and lymphatic system diseases， eye organ diseases， and infectious and invasive diseases； before using melphalan， it is necessary to evaluate the drug use of patients， and pay close attention to the patient’s blood indicators and eye toxicity reaction， so as to guarantee the safety of treatment.

Mining and analysis for adverse drug event signals of liver failure in underage population based on the FAERS database / 中国药房

OBJECTIVE To conduct data mining on drugs causing liver failure in underage populations based on the FDA Adverse Event Reporting System （FAERS） database， so as to provide reference for clinical use of related drugs. METHODS The data on reported adverse drug event （ADE） of liver failure in this population （under 18 years old） from the first quarter of 2013 to the third quarter of 2022 were retrieved from the FAERS database for mining and analysis； they were divided into infants（≤1 year old）， young children（＞1-＜6 years old）， children（6-＜12 years old） and adolescents（12-＜18 years old） according to the age. The reporting odds ratio （ROR）， proportional reporting ratio and Bayesian confidence propagation neural network of the proportional imbalance method were used to screen ADE signals. RESULTS A total of 1 051 ADE reports of liver failure were collected from the underage population involving 60 drugs. The highest incidence was found in adolescents （410 cases， 39.01%）， followed by young children （297 cases， 28.26%）. The instructions of 14 drugs did not mention hepatobiliary system injury and liver failure risk， including 31 cases of levetiracetam （2.95%），18 cases of metronidazole （1.71%）， 16 cases of each of topiramate and methylprednisolone （1.52% each）， 12 cases of dexamethasone （1.14%）， 11 cases of tisagenlecleucel （1.05%）， 10 cases of each of ferrous sulfate， metformin and busulfan （0.95% each）， 9 cases of propofol （0.86%）， 8 cases of onasemnogene abeparvovec （0.76%）， 5 cases of each of diphenhydramine and omeprazole （0.48% each）， 4 cases of sebeliesterase α （0.38%）， totaling 165 cases， accounting for 15.70% of the total reported cases. Metformin was contrary to the known liver safety， and E-mail：libingchemical@163.com metronidazole and levetiracetam were new risk signals， which caused more serious clinical outcomes. CONCLUSIONS Fourteen new pharmacovigilance signals which cause liver failure in the underage population are found in this study； the liver function of patients should be closely monitored when using these drugs. Among those drugs， metformin neither undergoes liver metabolism nor has been reported in the relevant literature， and the liver-related ADE caused by metformin deserves further attention. The clinical outcomes caused by metronidazole and levetiracetam are relatively serious and need to be given sufficient attention.

TCM Treatment Rule of Lung Cancer in Hubei Cancer Hospital Based on Data Mining and Complex Network Analysis / 肿瘤防治研究

Objective To explore the medication for lung cancer treatment at Hubei Cancer Hospital. Methods The electronic cases of 3 234 hospitalized lung cancer patients in Hubei Cancer Hospital were collected. The medication of the Peiyuan Guben method in treating lung cancer was analyzed with cluster and association analyses by the Apriori association rule algorithm in IBM SPSS modeler 18.0 and Qihuang data AI workstation software system. Results In the 11 293 pieces of traditional Chinese medicine used in 3 234 patients with lung cancer, the core prescription of 16 core drugs were Astragalus, Coix seed, Poria, Coke hawthorn, Ligustrum lucidum, Wolfberry, Bran fried atractylodes, Mushroom stem, Bran fried citrus husk, Bittersweet herb, Centipede, Rhodiola, Semiaquilegia adoxoides, Seaweed, Prunella and Pseudobulbus cremastrae seu pleiones. Conclusion "Peiyuan Guben" is an effective method of traditional Chinese medicine in treating lung cancer. Traditional Chinese medicine with the effects of Yiqi Jianpi and Bushen Yijing has an evident curative effect in treating lung cancer and can improve patients' quality of life.

Analysis of medication rules of TCM for perimenopausal syndrome based on literature mining / 药学实践杂志

Objective To investigate the rules of Traditional Chinese Medicine in the treatment of perimenopausal syndrome (PMS) and provide a theoretical basis for the clinical treatment of PMS. Methods The literature related to PMS were collected from China Knowledge Network (CNKI), Wanfang database and Weipu database in the past 20 years, the herbal compound prescriptions for the treatment of PMS were screened and a relevant database were established and analyzed by SPSS. Results The relevant literatures contains 184 Chinese medicine prescriptions/proprietary Chinese medicines, 122 flavors of traditional Chinese medicines, and the drug categories were mainly tonic drugs, antipyretic drugs, astringent drugs, and tranquilizers. The core single-flavor Chinese medicines were Baishao(Radix Paeoniae Alba), Shudihuang(Rehmannia glutinosa ), Danggui(Radix Angelicae Sinensis), Fuling (Indian Buead). The property and flavor covered sweet, bitter, cold, etc.; and the channel tropism belonged to the liver, kidneys, heart, lungs, spleen and meridians. The cluster analysis of high-frequency Traditional Chinese Medicine obtained two main combinations. Conclusion TCM treatment of PMS focused on replenishing qi, soothing the liver, nourishing the kidneys, nourishing blood and calming the heart, and then according to clinical compatibility with drugs such as soothing the nerves, clearing heat and removing dampness; most of its clinical treatment were Xiaoyaosan, Liuwei Dihuang pills, and Zhibo Rehmanniae decoction and other prescriptions which were added and subtracted.

Acupoint selection rules of acupuncture and moxibustion for post-stroke epilepsy based on data mining technology / 中国针灸

OBJECTIVE@#To analyze the acupoint selection rules of acupuncture and moxibustion for post-stroke epilepsy by data mining technology.@*METHODS@#The literature regarding acupuncture and moxibustion for post-stroke epilepsy included in CNKI, VIP, Wanfang, SinoMed and PubMed databases from the establishment of the database to August 1st 2022 was retrieved. Microsoft Excel 2019 software was used to establish a database to conduct the descriptive analysis of acupoints; SPSS Modeler 18.0 Apriori algorithm was used to conduct association rule analysis; high-frequency acupoint co-occurrence network diagrams were drawn by Cytoscape3.9.0 software; SPSS Statistics 25.0 software was used to perform hierarchical cluster analysis on high-frequency acupoints and a tree diagram was drawn.@*RESULTS@#Totally 39 articles were included, and 63 prescriptions of acupuncture and moxibustion were extracted, involving 56 acupoints, with a total frequency of 516 times; the top three acupoints with the highest frequency of use were Baihui (GV 20), Fenglong (ST 40) and Neiguan (PC 6); the selected meridians were mainly the governor vessel, the hand and foot yangming meridians; the selection of acupoints were mostly in the head, neck and lower limbs; in terms of acupoint compatibility, Hegu (LI 4)-Shuigou (GV 26) and Neiguan (PC 6) had the highest confidence degree; The top 20 high-frequency acupoints could be divided into 4 effective clusters.@*CONCLUSION@#Modern acupuncture and moxibustion treatment for post-stroke epilepsy attaches great importance to the use of yang meridians and meridians with enrich qi and blood; the core prescription is Shuigou (GV 26)-Neiguan (PC 6)-Hegu (LI 4)-Baihui (GV 20). In addition, the combination of distant and near acupoints is highly valued to improve clinical efficacy.

The rules of acupoint selection of acupuncture and moxibustion for aphasia based on data mining / 中国针灸

OBJECTIVE@#To explore the rules of acupoint selection for aphasia treated with acupuncture and moxibustion using data mining technology.@*METHODS@#From January 1, 2000 to April 1, 2022, the articles for clinical researches of acupuncture and moxibustion for aphasia published in CNKI, Wanfang, VIP, SinoMed, PubMed, EMbase were searched. Using Microsoft Excel 2021, the database was set up to analyze the use frequency of acupoint, meridian tropism, acupoint distribution and the use of specific points. SPSS26.0 was adopted for factor analysis, SPSS Modeler 18.0 was for association rule analysis of prescriptions, and Gephi 0.9.5 was to plot the co-occurrence network diagrams of acupoints and meridians.@*RESULTS@#A total of 140 articles were collated, including 146 acupuncture and moxibustion prescriptions and 189 acupoints. The total use frequency of these acupoints was 1 211. Lianquan (CV 23), Jinjin (EX-HN 12), Yuye (EX-HN 13), Baihui (GV 20) and Yamen (GV 15) were the top 5 acupoints of the high use frequency for aphasia treated with acupuncture and moxibustion. Among 189 acupoints collected, the extra points and empirical points were mostly selected. The top 3 involved meridians were the governor vessel, the gallbladder meridian of foot-shaoyang and the conception vessel. These acupoints were mostly distributed on the head, face and neck region. The use frequency of five-shu points was the highest among the specific points. The acupoint combinations of high frequency referred to Yuye (EX-HN 13)-Jinjin (EX-HN 12), Yuye (EX-HN 13)-Lianquan (CV 23)-Jinjin (EX-HN 12), and Fengchi (GB 20)-Yuye (EX-HN 13)-Jinjin (EX-HN 12). Factor analysis extracted 10 common factors for acupoint compatibility in treatment of aphasia with acupuncture and moxibustion.@*CONCLUSION@#In clinical treatment of aphasia with acupuncture and moxibustion, the local acupoints are preferred. The core acupoints include Lianquan (CV 23), Jinjin (EX-HN 12), Yuye (EX-HN 13), Baihui (GV 20) and Yamen (GV 15). The acupoint prescription is modified flexibly according to syndrome differentiation to enhance the therapeutic effect.

Animal Model of Premature Ovarian Insufficiency Based on Data Mining / 中国实验方剂学杂志

ObjectiveTo study the modeling characteristics of the animal model of premature ovarian insufficiency and provide references for the standardization of the animal model of premature ovarian insufficiency， thus offering a better research basis to the pathogenesis， diagnosis， and treatment of the disease. MethodThe animal experimental literature of premature ovarian insufficiency in the past decade was obtained by searching China National Knowledge Infrastructure （CNKI）， Wanfang， VIP Chinese Technology Periodical Database， China Biology Medicine （CBM）， and PubMed. The types of experimental animals， modeling methods， dosage， administration scheme， modeling standards， and detection indicators were summarized. The frequency analysis was performed with Excel， the association rule analysis was performed with SPSS Modeler 18.0， and the results were visually upgraded with Cytascape 3.6.1. ResultA total of 281 articles were included， and most animal experiments on premature ovarian insufficiency were performed on SD rats or BALB/c mice. Most modeling methods were iatrogenic induction， and the main modeling drug was cyclophosphamide. Erestrous cycle disorder was selected as the modeling standard. Ovarian histomorphology， estradiol， follicle stimulating hormone， and estrous cycle were selected as the detection indicators to comprehensively evaluate the model from multiple aspects. ConclusionSD rats are mostly used to induce modeling in animal experiments on premature ovarian insufficiency through first intraperitoneal injection of cyclophosphamide 50 mg·kg-1 and 8 mg·kg-1·d-1 from the next day for 14 d， which has the advantages of easy operation， high modeling rate， and consistency with the disease pathogenesis. This paper can provide references for basic animal experimental research of premature ovarian insufficiency.

Analysis of medication rules of traditional Chinese medicine in treatment of renal anemia based on data mining / 中国药房

OBJECTIVE To carry out data mining on the prescriptions of traditional Chinese medicine （TCM） for the treatment of renal anemia， and to explore the medication rules of TCM in the treatment of renal anemia. METHODS The Chinese and English databases including PubMed， the Cochrane Library， Web of Science， CNKI， Wanfang， VIP and CBM were searched by computer to screen the related literature about TCM in the treatment of renal anemia. Excel software was used to extract prescription information， including frequency of use， property and flavor， meridian tropism and efficacy of single TCM. Association rule analysis and hierarchical clustering analysis were performed for each ingredient of TCM with R language. RESULTS A total of 268 literature were included， involving 169 ingredients with a total use frequency of 3 919 times. Among them， Astragalus memeranaceus， Angelica sinensis， Atractylodes macrocephala， Rheum officinale， Poria cocos， Radix Rehmanniae Praeparata， Radix Codonopsis， Salvia miltiorrhiza and Ligusticum chuanxiong were used more than 100 times. The properties and flavors of the drugs were mainly warm and sweet； meridian tropism mainly targeted spleen， liver and kidney； the function was mainly in replenishing qi， nourishing blood， promoting blood circulation and removing blood stasis， and clearing damp and promoting diuresis， purgation. The result of association rule analysis showed that the core ingredients were A. memeranaceus， A. sinensis， A. macrocephala， P. cocos and S. miltiorrhiza. Hierarchical cluster analysis showed that the clustering results were divided into grade 1， 2 and 3， and the cluster classification of A. memeranaceus and A. sinensis was always the same. CONCLUSIONS The core prescription for treating renal anemia includes A. memeranaceus， A. sinensis， A. macrocephala， P. cocos and S. miltiorrhiza； among them， A. memeranaceus and A. sinensis are at the center of the core prescription and indispensable. The medication rule is mainly guided by drugs for invigorating qi， nourishing blood， strengthening spleen， and removing dampness. According to the characteristics of different symptoms of patients， dialectical treatment is made， and other TCM is added or subtracted on the basis of the core prescription.

Analysis of Medication Rules of Traditional Chinese Medicine for Malaria Treatment Based on Data Mining / 中国医学科学杂志(英文版)

Objective To analyze the medication rules of traditional Chinese medicine (TCM) for malaria treatment.Methods Statistical analysis was conducted on the basic attributes of TCM drugs with regard to property, therapeutic methods, flavor, and meridian tropism. A complex network of TCM drug associations was constructed. Cluster analysis was applied to obtain the core drugs for malaria treatment. The Apriori algorithm was applied to analyze the association rules of these core drugs.Results A total of 357 herbs were used 3,194 times in 461 prescriptions for malaria treatment. Radix Glycyrrhizae (), Rhizoma Pinelliae (), Radix Bupleuri (), and Radix Dichroae () were the frequently used herbs through supplementing, exterior-releasing, heat-clearing, qi-rectifying, and damp-resolving therapeutic methods. Such herbs had warm, natural, and cold herbal properties; pungent, bitter, and sweet flavors; and spleen, lung, and stomach meridian tropisms. Cluster analysis showed 61 core drugs, including Radix Glycyrrhizae, Rhizoma Pinelliae, Radix Bupleuri, and Radix Scutellariae (). Apriori association rule analysis yielded 12 binomial rules (herb pairs) and 6 trinomial rules (herb combinations). Radix Bupleuri plus Radix Scutellariae was the core herbal pair for treating malaria. This pair could be combined with Rhizoma Atractylodis Macrocephalae () for treating warm or cold malaria, combined with Pericarpium Citri Reticulatae () or Radix Dichroae () for treating miasmic malaria, or combined with turtle shells () for treating malaria with splenomegaly.Conclusions TCM can be used to classify and treat malaria in accordance with the different stages of development. As the core herbal pair, Radix Bupleuri and Radix Scutellariae can be combined with other drugs to treat malaria with different syndrome types.

Medication rules of Chinese herbal compound prescriptions for treating angina in national patent database based on multiple data mining / 中国中药杂志

This study explored the medication rules of Chinese herbal compound prescriptions for the treatment of angina based on the Chinese herbal compound patents in the patent database of the China National Intellectual Property Administration. The data of eligible Chinese herbal compound patents for the treatment of angina were collected from the patent database of the China National Intellectual Property Administration from database inception to November 10, 2022, and subjected to data modeling, analysis of main syndromes, medication frequency analysis, cluster analysis, association rule analysis, and data visualization by using Excel 2021, IBM SPSS Statistics 26.0, IBM SPSS Modeler 18.0, Cytoscape 3.9.1, and Rstudio R 4.2.2.2 to explore the medication rules for angina. The study included 636 pieces of patent data for angina that met the inclusion criteria, involving 815 drugs, with a total frequency of 6 586. The most common main syndromes were blood stasis obstructing the heart syndrome(222, 34.91%) and Qi deficiency and blood stasis syndrome(112, 17.61%). The top 10 most frequently used drugs were Salviae Miltiorrhizae Radix et Rhizoma, Chuanxiong Rhizoma, Notoginseng Radix et Rhizoma, Astragali Radix, Angelicae Sinensis Radix, Carthami Flos, Glycyrrhizae Radix et Rhizoma, Ginseng Radix et Rhizoma, Borneolum Syntheticum, and Corydalis Rhizoma. High-frequency drugs included blood-activating and stasis-resolving drugs(1 197, 18.17%) and deficiency-tonifying drugs(809, 12.28%). Cluster analysis identified eight drug combinations, including five new prescriptions suitable for clinical use and new drug development, and three drug pairs. The core drug combination of Salviae Miltiorrhizae Radix et Rhizoma-Chuanxiong Rhizoma-Carthami Flos was identified through the complex co-occurrence network analysis of Chinese medicines. Association rule analysis yielded a total of 17 rules, including 13 drug pairs and 4 tripartite combinations. Common drug pairs included Salviae Miltiorrhizae Radix et Rhizoma-Chuanxiong Rhizoma(support degree 25.79%, confidence coefficient 69.49%, lift 1.30) and Salviae Miltiorrhizae Radix et Rhizoma-Notoginseng Radix et Rhizoma(support degree 22.01%, confidence coefficient 61.95%, lift 1.16). Common tripartite combinations included Salviae Miltiorrhizae Radix et Rhizoma-Chuanxiong Rhizoma-Astragali Radix(support degree 10.85%, confidence coefficient 73.40%, lift 1.37) and Salviae Miltiorrhizae Radix et Rhizoma-Chuanxiong Rhizoma-Notoginseng Radix et Rhizoma(support degree 10.69%, confidence coefficient 79.07%, lift 1.48). The results showed that the underlying pathogenesis of angina involved blood stasis obstructing the heart and Qi deficiency and blood stasis. The overall nature of the disease was characterized as asthenia in origin and sthenia in superficiality. In the prescription formulation, blood-activating and stasis-resolving drugs, such as Salviae Miltiorrhizae Radix et Rhizoma, Chuanxiong Rhizoma, and Carthami Flos were often used to resolve the excess manifestation, which were combined with tonifying drugs such as Astragali Radix, Angelicae Sinensis Radix, Glycyrrhizae Radix et Rhizoma, and Ginseng Radix et Rhizoma to reinforce the deficiency. The syndrome, pathogenesis, disease nature, and medication were consistent with clinical practice. Additionally, the new compound prescriptions and drug combinations derived from the multiple data mining in this study could provide references and insights for the clinical diagnosis and treatment of angina and the development of new drugs.

Prescription and medication rules of traditional Chinese medicine for prevention and treatment of diabetic microangiopathy based on literature mining / 中国中药杂志

This study explored the prescription and medication rules of traditional Chinese medicine(TCM) in the prevention and treatment of diabetic microangiopathy based on literature mining. Relevant literature on TCM against diabetic microangiopathy was searched and prescriptions were collected. Microsoft Excel 2021 software was used to establish a prescription database, and an analysis was conducted on the frequency, properties, flavors, meridian tropism, and efficacy classifications of drugs. Association rule analysis, cluster analysis, and factor analysis were performed using SPSS Modeler 18.0 and SPSS Statistics 26.0 software. The characteristic active components and mechanisms of action of medium-high frequency drugs in the analysis of medication rules were explored through li-terature mining. A total of 1 327 prescriptions were included in this study, involving 411 drugs, with a total frequency reaching 19 154 times. The top five high-frequency drugs were Astragali Radix, Angelicae Sinensis Radix, Poria, Salviae Miltiorrhizae Radix et Rhizoma, and Rehmanniae Radix. The cold and warm drugs were used in combination. Drugs were mainly sweet, followed by bitter and pungent, and acted on the liver meridian. The majority of drugs were effective in tonifying deficiency, clearing heat, activating blood, and resolving stasis. Association rule analysis identified the highly supported drug pair of Astragali Radix-Angelicae Sinensis Radix and the highly confident drug combination of Poria-Alismatis Rhizoma-Corni Fructus. The strongest correlation was found among Astragali Radix, Angelicae Sinensis Radix, Poria, and Salviae Miltiorrhizae Radix et Rhizoma through the complex network analysis. Cluster analysis identified nine categories of drug combinations, while factor analysis identified 16 common factors. The analysis of active components in high-frequency drugs for the treatment of diabetic microangiopathy revealed that these effective components mainly exerted their effects by inhibiting oxidative stress and suppressing inflammatory reactions. The study found that the pathogenesis of diabetic microangiopathy was primarily characterized by deficiency in origin, with a combination of deficiency and excess. Deficiency was manifested as Qi deficiency and blood deficiency, while excess as phlegm-heat and blood stasis. The key organ involved in the pathological changes was the liver. The treatment mainly focused on supplementing Qi and nourishing blood, supplemented by clearing heat, coo-ling blood, activating blood, and dredging collaterals. Commonly used formulas included Danggui Buxue Decoction, Liuwei Dihuang Pills, Erzhi Pills, and Buyang Huanwu Decoction. The mechanisms of action of high-frequency drugs in the treatment of diabetic microangiopathy were often related to the inhibition of oxidative stress and suppression of inflammatory reactions. These findings can provide references for the clinical treatment of diabetic microangiopathy and the development of targeted drugs.