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.

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.

Design of early warning system for mental health problems based on data mining and database / Projeto de sistema de alerta precoce para problemas de saúde mental com base na mineração de dados e banco de dados / Diseño de un sistema de alerta temprana de problemas de salud mental basado en la minería de datos y en la base de datos

ABSTRACT Introduction: Data mining technology is mainly employed in the era of big data to evaluate the acquired information. Subsequently, reasoning about the data inductively is fully automated to discover possible patterns. Objective: Recently, data mining technology in the national mental health database has deepened and can be effectively used to solve various mental health early warning problems. Methods: For example, it can be applied to mine psychological data and extract the most important features and information. Results: This paper presents the design of an early warning system for mental health problems based on data mining techniques to offer some thoughts on early warning of mental health problems, including data preparation, data mining, results in analysis, and decision tree algorithm. Conclusion: The experimental results indicate that the results of the early warning system in this paper can achieve an accuracy rate of more than 96% with a high accuracy rate. Level of evidence II; Therapeutic studies - investigating treatment outcomes.

RESUMO Introdução: A tecnologia de mineração de dados é empregada principalmente na era da big data para avaliar as informações adquiridas. Posteriormente, raciocinar indutivamente sobre os dados de forma totalmente automatizada para descobrir possíveis padrões. Objetivo: Recentemente, a tecnologia de mineração de dados no banco de dados nacional de saúde mental tem se aprofundado e pode ser efetivamente utilizada para resolver vários problemas de alerta precoce da saúde mental. Métodos: Por exemplo, ela pode ser aplicada para a mineração de dados psicológicos e extrair as características e informações mais importantes. Resultados: Este documento apresenta o projeto de um sistema de alerta precoce para problemas de saúde mental baseado em técnicas de mineração de dados, com o objetivo de oferecer algumas reflexões sobre alerta precoce de problemas de saúde mental, incluindo preparação de dados, mineração de dados, análise de resultados e algoritmo de árvore de decisão. Conclusão: Os resultados experimentais indicam que os resultados do sistema de alerta precoce neste trabalho podem alcançar uma taxa de precisão de mais de 96% com uma alta taxa de precisão. Nível de evidência II; Estudos terapêuticos - investigação dos resultados do tratamento.

Resumen Introducción: La tecnología de minería de datos se emplea principalmente en la era de la big data para evaluar la información adquirida. Posteriormente, razonar inductivamente sobre los datos de forma totalmente automatizada para descubrir posibles patrones. Objetivo: Recientemente, la tecnología de minería de datos en la base de datos nacional de salud mental se ha profundizado y puede ser utilizada eficazmente para resolver varios problemas de alerta temprana de salud mental. Métodos: Por ejemplo, puede aplicarse para minar datos psicológicos y extraer las características e información más importantes. Resultados: Este trabajo presenta el diseño de un sistema de alerta temprana de problemas de salud mental basado en técnicas de minería de datos, con el objetivo de ofrecer algunas reflexiones sobre la alerta temprana de problemas de salud mental, incluyendo la preparación de los datos, la minería de datos, el análisis de los resultados y el algoritmo de árbol de decisión. Conclusión: Los resultados experimentales indican que los resultados del sistema de alerta temprana de este documento pueden alcanzar un índice de precisión superior al 96% con un alto índice de precisión. Nivel de evidencia II; Estudios terapéuticos - investigación de los resultados del tratamiento.

Application analysis of digital neural network-based data mining method in maximizing the performance of sports training / Análise de aplicação do método de mineração de dados baseado em rede neural digital na maximização do desempenho do treinamento esportivo / Análisis de la aplicación del método de minería de datos basado en redes neuronales digitales para maximizar el rendimiento del entrenamiento deportivo

ABSTRACT Introduction: In today's rapid development of science and technology, digital network data mining technology is developing as fast as the expansion of the frontiers of science and technology allows, with a very broad application level, covering most of the civilized environment. However, there is still much to explore in the application of sports training. Objective: Analyze the feasibility of data mining based on the digital network of sports training, maximizing athletes' training. Methods: This paper uses the experimental analysis of human FFT, combined with BP artificial intelligence network and deep data mining technology, to design a new sports training environment. The controlled test of this model was designed to compare advanced athletic training modalities with traditional modalities, comparing the athletes' explosive power, endurance, and fitness. Results: After 30 days of physical training, the athletic strength of athletes with advanced fitness increased by 15.33%, endurance increased by 15.85%, and fitness increased by 14.23%. Conclusion: The algorithm designed in this paper positively impacts maximizing athletes' training. It may have a favorable impact on training outcomes, as well as increase the athlete's interest in the sport. Level of evidence II; Therapeutic studies - investigating treatment outcomes.

RESUMO Introdução: No rápido desenvolvimento atual de ciência e tecnologia, a tecnologia de mineração de dados de rede digital desenvolve-se tão rápido quanto a expansão das fronteiras da ciência e tecnologia permitem, com um nível de aplicação muito amplo, cobrindo a maior parte do ambiente civilizado. No entanto, ainda há muito para explorar da aplicação no treinamento esportivo. Objetivo: Análise de viabilidade da mineração de dados com base na rede digital da formação esportiva, maximizar o treinamento dos atletas. Métodos: Este trabalho utiliza a análise experimental da FFT humana, combinada com a rede de inteligência artificial da BP e tecnologia de mineração profunda de dados, para projetar um novo ambiente de treinamento esportivo. O teste controlado deste modelo foi projetado para comparar modalidades avançadas de treinamento atlético com as modalidades tradicionais, comparando o poder explosivo, resistência e condição física do atleta. Resultados: Após 30 dias de treinamento físico, a força atlética dos esportistas com aptidão física avançada aumentou 15,33%, a resistência aumentou 15,85%, e o condicionamento físico aumentou 14,23%. Conclusão: O algoritmo desenhado neste artigo tem um impacto positivo na maximização do treinamento dos atletas. Pode ter um impacto favorável nos resultados do treinamento, bem como aumentar o interesse do atleta pelo esporte. Nível de evidência II; Estudos terapêuticos - investigação dos resultados do tratamento.

RESUMEN Introducción: En el rápido desarrollo actual de la ciencia y la tecnología, la tecnología de extracción de datos de redes digitales se desarrolla tan rápido como lo permiten las fronteras en expansión de la ciencia y la tecnología, con un nivel de aplicación muy amplio que abarca la mayor parte del entorno civilizado. Sin embargo, aún queda mucho por explorar de la aplicación en el entrenamiento deportivo. Objetivo: Análisis de viabilidad de la minería de datos basada en la red digital de entrenamiento deportivo, maximizar la formación de los atletas. Métodos: Este trabajo utiliza el análisis experimental de la FFT humana, combinado con la red de inteligencia artificial BP y la tecnología de minería de datos profunda, para diseñar un nuevo entorno de entrenamiento deportivo. La prueba controlada de este modelo se diseñó para comparar las modalidades de entrenamiento atlético avanzado con las modalidades tradicionales, comparando la potencia explosiva, la resistencia y la forma física del atleta. Resultados: Después de 30 días de entrenamiento físico, la fuerza atlética de los atletas con un estado físico avanzado aumentó en un 15,33%, la resistencia aumentó en un 15,85% y el estado físico aumentó en un 14,23%. Conclusión: El algoritmo diseñado en este trabajo tiene un impacto positivo en la maximización del entrenamiento de los atletas. Puede tener un impacto favorable en los resultados del entrenamiento, así como aumentar el interés del atleta por el deporte. Nivel de evidencia II; Estudios terapéuticos - investigación de los resultados del tratamiento.

Medication and prescription rules for treating spleen and stomach diseases in Prescriptions of Peaceful Benevolent Dispensary / 数字中医药（英文）

@#【Objective】   To explore the prescriptions related to the treatment of spleen and stomach diseases in Prescriptions of Peaceful Benevolent Dispensary (Tai Ping Hui Min He Ji Ju Fang,《太平惠民和剂局方》, TPHMHJJF), and investigate the medication and prescription rules. 【Methods】   The prescriptions of TPHMHJJF for treating spleen and stomach diseases were screened, and the data set was established by entering the prescriptions and standardized drug names using WPS Excel 2019. Herb frequency statistics, efficacy categorization, property, flavor, meridian tropism, association rules, cluster analysis, factor analysis, and complex network analysis were performed using Python 3.6.8 programming language and Gephi 0.9.2 visualization software. 【Results】   A total of 239 prescriptions were included after the screening, and the dosage forms were mainly pills and powders. The study involved 200 herbal medicines, among which 40 herbs had a frequency of ≥ 12. The herb with the highest frequency was Ganjiang (Zingiber Rhizoma). The herb properties were mainly warm in nature, with the most pungent herbs. Most herbs were attributed to the spleen and stomach meridians, and tonifying medicine were the main species. The association rule analysis identified 26 second-order association rules and 16 third-order association rules, with "Renshen (Ginseng Radix et Rhizoma) → Fuling (Poria)" as the leading rule in the former and "Fuling (Poria) + Baizhu (Atractylodis Macrocephalae Rhizome) → Renshen (Ginseng Radix et Rhizoma)" as the leading rule in the latter. Also, cluster analysis divided the top 30 herbs into six herb combinations that can warm the middle, move Qi, and dry dampness effectively. Factor analysis extracted 13 common factors, with Renshen (Ginseng Radix et Rhizoma), Fuling (Poria), and Baizhu (Atractylodis Macrocephalae Rhizome) as the highest contributing factors. Lastly, complex network analysis yielded the core prescription of 14 herbs, with Ganjiang (Zingiber Rhizoma), Renshen (Ginseng Radix et Rhizoma), Gancao (Glycyrrhizae Radix et Rhizome), and Chenpi (Citri Reticulatae Pericarpium) among the herbs with a higher weighting degree. 【Conclusion】  TPHMHJJF is mainly based on the use of warming herbs to treat spleen and stomach diseases, and its medication rule can be summarized into three aspects: (i) primarily using warming and tonifying to warm the middle and dissipate cold, (ii) using the method of moving Qi with aromatic nature to delight the spleen and appetize the stomach, and (iii) emphasizing the regulation of Qi and blood to calm the five zang-organs.

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.

Signal detection and analysis of the adverse events of ustekinumab based on OpenFDA database / 中国药房

OBJECTIVE To analyze the risk of adverse drug reaction of ustekinumab， so as to provide reference for rational drug use in clinic. METHODS The adverse events （AE） reports related to ustekinumab included in the FDA public data program （OpenFDA） database were analyzed after marketing （from September 25th 2009 to December 30th 2021）. The risk signals were mined for top 100 AE by the method of reporting odds ratio （ROR） and proportional reporting ratio （PRR）. RESULTS A total of 62 356 AE reports related to ustekinumab were retrieved， male patients （51.79%） were more than female patients （39.51%）. Results of ROR method and PRR method showed that 31 suspicious signals were mined， mainly infections and infectious diseases （9 kinds）， general disorders and administration site conditions （5 kinds）， skin and subcutaneous tissue disorders diseases （4 kinds）， musculoskeletal and connective tissue disorders （4 kinds）， etc. Fourteen suspicious signals were not included in the instructions， such as hepatic enzyme increase， basal cell carcinoma， pericarditis， pemphigus， hair loss， synovitis， glossodynia， etc. CONCLUSIONS During clinical dosing of ustekinumab， in addition to ADR mentioned in package inserts， great attention should be paid to the patient’s liver function， skin status， hair loss and cardiovascular-related risks，which is helpful to discover AE early and ensure the safety medication of patients.

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.

Evidence and acupoint combinations in acupuncture for functional dyspepsia: an overview of systematic review and data mining study / 数字中医药（英文）

Objective@#To evaluate the methodological quality of papers that performed meta-analyzed and systematically reviewed acupoint selections for the treatment of functional dyspepsia (FD) and to identify the ideal acupoint combinations for FD.@*Methods@#Chinese databases including China National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database (VIP), China Biology Medicine (CBM), and Wanfang Database, as well as English databases including PubMed, Embase, and Cochrane Library were searched to retrieve papers about meta-analysis and systematic literature reviews on acupuncture for FD. The time span for the paper retrieval was set from the foundation of the databases to April 30, 2022. The Veritas scores of the papers based on their publication year, study type, Assessment of Multiple Systematic Reviews 2 (AMSTAR2), Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), heterogeneity, and publication bias were rated to assess the methodological quality of the included studies. Then, randomized controlled trials (RCTs) were extracted from those meta-analysis papers or systematic literature reviews for analyzing acupoints frequency, meridian frequency, and association rules with the use of R software (V 4.3.1).@*Results@#Eight meta-analysis papers were included in the study after screening. The mean Veritas scores of the papers based on publication year, type of study, AMSTAR2, PRISMA, heterogeneity, and publication bias were 4.50, 8.00, 4.63, 4.63, 4.50, and 6.13, respectively. The analysis of the scores revealed insufficiencies in the reviews pertaining to the methodology, comprehension of the research strategy, detailed list of excluded studies, sources of funding, assessment of potential bias risks impact on meta-analysis results in each study, explanation of heterogeneity, and identification of potential conflicts of interest. Furthermore, a total of 85 RCTs were obtained from the eight meta-analysis papers involving 85 acupuncture prescriptions and 67 acupoints for subsequent data mining. The most commonly used meridian was Stomach meridian of Foot-Yangming (ST). Zusanli (ST36), Neiguan (PC6), Zhongwan (CV12), Taichong (LR3), Tianshu (ST25), Gongsun (SP4), Weishu (BL21), Pishu (BL20), Neiting (ST44), and Yinlingquan (SP9) topped the list of frequently selected acupoints. Additionally, a total of 28 association rules were identified, including 10 second-order, 15 third-order, and 3 fourth-order association rules. The top-ranking association rules in each order were “Neiguan (PC6) → Zusanli (ST36)” “Zhongwan (CV12) + Neiguan (PC6) → Zusanli (ST36)” and “Zhongwan (CV12) + Taichong (LR3) + Neiguan (PC6) → Zusanli (ST36)”, respectively.@*Conclusion@#Acupuncture could alleviate the clinical symptoms of FD. However, the quality of methodology applied in the meta-analysis papers on the subject needs to be improved. Through data mining, a combination of Neiguan (PC6), Zusanli (ST36), Zhongwan (CV12), and Taichong (LR3) was identified as an essential acupoint combination for the treatment of FD.

Acupoints compatibility rules of acupuncture for depression disease based on data mining technology / 中国针灸

Based on data mining technology, the acupoints compatibility rules of acupuncture for depression diseases were explored. The randomized controlled trial (RCT) articles regarding acupuncture for depression diseases published from establishment of database to September 2nd, 2022 were searched in CNKI database, Wangfang database, VIP database, SinoMed database, PubMed, EMbase, Web of Science and Cochrane Library. The use frequency of acupoints, meridian tropism, selection of special acupoints and acupoint association rules for five common depression diseases, including primary depression, post-stroke depression, menopausal syndrome, psychoneurosis and anxiety disorder, were analyzed by Python programming language. Cytoscape software was used to analyze the acupoint association and the disease-acupoint co-occurrence network. As a result, totally 387 articles were included, and 319 acupoints prescriptions for the above five common depression diseases were extracted, involving 159 acupoints. The use frequency of acupoints was 2 574 times in total. The frequently-used acupoints were Baihui (GV 20), Sanyinjiao (SP 6), Taichong (LR 3), Neiguan (PC 6), Shenmen (HT 7), Yintang (GV 24+), Zusanli (ST 36), Hegu (LI 4), Sishencong (EX-HN 1) and Taixi (KI 3), etc. The frequently involved meridians were the governor vessel, foot-taiyang bladder meridian, foot-taiyin spleen meridian, and foot-jueyin liver meridian. The frequency of the special acupoints from high to low was crossing points, five-shu points, yuan-primary points, back-shu points, luo-connecting points, and eight confluent points, etc, which were often used in combination with "Baihui (GV 20)-Yintang (GV 24+)" (the highest degree of association). At the same time, the analysis of the co-occurrence network of depression diseases and acupoints showed that the core acupoints group of acupuncture for depression diseases were Baihui (GV 20), Taichong (LR 3), Shenmen (HT 7), Zusanli (ST 36), Neiguan (PC 6) and Sanyinjiao (SP 6). In conclusion, acupuncture treatment for depression diseases has gradually formed a rule of acupoint compatibility, with special acupoint as the main body and "unblocking the governor vessel, and regulating the spirit and qi " as the main therapeutic principle.

The rules of acupoint selection of acupuncture and moxibustion for scrofula in ancient times / 中国针灸

Based on data mining technology, the rules of acupoint selection of acupuncture-moxibustion for scrofula in ancient times were analyzed. The relevant articles of acupuncture and moxibustion for scrofula were searched in the Chinese Medical Code, and the original article, acupoint name, acupoint characteristic, and acupoint meridian tropism, etc. were screened and extracted. The Microsoft Excel 2019 was used to establish a acupoint prescription database, and the frequency of acupoints as well as their meridian tropism and characteristics were analyzed. The SPSS21.0 was applied to perform cluster analysis of acupuncture prescriptions; the SPSS Modeler 18.0 was used to perform the association rules analysis of the neck and the chest-armpit acupoints, respectively. As a result, 314 acupuncture prescriptions were extracted, including 236 single-acupoint prescriptions and 78 multiple-acupoints prescriptions (53 for neck and 25 for chest-armpit). A total of 54 acupoints were involved, with a total frequency of 530. The top 3 commonly-used acupoints were Tianjing (TE 10), Zulinqi (GB 41) and Taichong (LR 3); the most commonly-used meridians were hand shaoyang meridian, foot shaoyang meridian, hand yangming meridian and foot yangming meridian; the most commonly-used special acupoints were he-sea points and shu-stream points. The cluster analysis obtained 6 clusters, and the association rule analysis obtained that the core prescriptions of the neck were Quchi (LI 11), Jianyu (LI 15), Tianjing (TE 10) and Jianjing (GB 21), while the core prescriptions of the chest-armpit were Daling (PC 7), Yanglingquan (GB 34), Danzhong (CV 17), Jianjing (GB 21), Waiguan (TE 5), Zhigou (TE 6), Yuanye (GB 22) and Zhangmen (LR 13). The core prescriptions obtained from association rule analysis by difference areas were basically consistent with those by cluster analysis of total prescriptions.

Application characteristics of Qugu (CV 2) in ancient and modern literature / 中国针灸

To summarize and analyze the clinical application characteristics of Qugu (CV 2) in ancient and modern literature based on data mining technology. The Chinese Medical Code (the 5th edition) was taken as the retrieval source of ancient literature, while the CNKI, Wanfang, and VIP databases were taken as the retrieval source of modern literature. The indications of Qugu (CV 2) used alone or with compatible acupoints, compatible acupoints, acupuncture-moxibustion manipulation, etc., were systematically sorted out. As a result, a total of 140 articles of ancient literature were included. The common indications of Qugu (CV 2) used alone were urinary retention, profuse vaginal discharge and hernia. The common indications of Qugu (CV 2) used with compatible acupoints were profuse vaginal discharge, stranguria and hernia. Sixty-four acupoints were concurrently used with Qugu (CV 2), Qugu (CV 2) was mainly compatible with acupoints of conception vessel, bladder meridian and liver meridian, and the high-frequency acupoints included Zhongji (CV 3), Guanyuan (CV 4) and Sanyinjiao (SP 6); five-shu points were the most used special acupoints, and moxibustion therapy was often used. A total of 73 modern articles were included. The common indications of Qugu (CV 2) used alone were urinary retention, erectile dysfunction and chronic prostatitis; the common indications of Qugu (CV 2) used with compatible scupoints were urinary retention, erectile dysfunction and prostatic hyperplasia. Thirty-six acupoints were concurrently used with Qugu (CV 2), Qugu (CV 2) was mainly compatible with acupoints of conception vessel, kidney meridian and spleen meridian, and the high-frequency acupoints included Zhongji (CV 3), Guanyuan (CV 4) and Zusanli (ST 36); front-mu points were the most used special acupoints, and acupuncture therapy was often used. Qugu (CV 2) treats a wide range of diseases in ancient times, the distant treatment effectiveness of acupoints is emphasized; and it mainly treats local diseases in modern times, the nearby treatment effectiveness of acupoints is emphasized.

Characteristics of Traditional Chinese Medicine Syndromes in 296 Patients with Urolithiasis / 中国实验方剂学杂志

ObjectiveTo analyze the characteristics of tradition Chinese medicine (TCM) syndromes in patients with urolithiasis. MethodA syndrome questionnaire was developed to collect the general data and four diagnosis information on 296 patients with urolithiasis who were treated from September 2021 to September 2022. Tongue images, pulse images, symptoms, and signs were statistically analyzed, and the characteristics of syndrome were explored by association rule analysis, factor analysis, and cluster analysis. Result① In the distribution of tongue images, the single tongue images with a frequency of more than 20% were white fur, red tongue, thick fur, greasy fur, and yellow fur. In the distribution pf pulse images, the single pulse with the frequency of more than 20% was fine pulse, string pulse, slippery pulse, and sinking pulse. There were 27 symptoms and signs with a frequency of more than 10%. The characteristic symptoms of acute onset such as lumbar and abdominal pain and nausea, frequent urination, hematuria, and poor urination were relatively common, and other symptoms were chill and fever, defecation, and digestion. ② Among the 14 strong association rules, 5 were yang-deficiency and cold-dampness syndromes, 4 were yin-deficiency and heat syndromes, 1 was kidney-deficiency syndrome, and 3 were renal colic with accompanying symptoms. ③ Sixteen common factors were extracted by factor analysis, and the main elements of the disease location were represented by spleen and kidney. The main elements of disease natures were Yin deficiency, Yang deficiency, dampness, and heat, and often mixed with deficiency-excess in complexity. Six syndromes were obtained by cluster analysis, and the represented syndromes were mainly kidney deficiency and dampness and stasis, Qi stagnation and heat accumulation, Yin deficiency and dampness heat, spleen-kidney Yang deficiency, spleen deficiency and dampness, and dampness-heat accumulation. ConclusionThe syndrome manifestations of urolithiasis are chill and fever, defecation, sweating, and digestive tract symptoms. The deficiency syndromes are mainly Yin deficiency, Yang deficiency, kidney deficiency, and spleen deficiency. The excess syndromes are mainly wet and heat. The deficiency and excess syndromes often exist simultaneously. The spleen deficiency is the important pathogenesis of urolithiasis besides the kidney deficiency.

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.