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Pediatric cough is a heterogeneous condition in terms of symptoms and the underlying disease mechanisms. Symptom phenotypes hold complicated interactions between each other to form an intricate network structure. This study aims to investigate whether the network structure of pediatric cough symptoms is associated with the prognosis and outcome of patients. A total of 384 cases were derived from the electronic medical records of a highly experienced traditional Chinese medicine (TCM) physician. The data were divided into two groups according to the therapeutic effect, namely, an invalid group (group A with 40 cases of poor efficacy) and a valid group (group B with 344 cases of good efficacy). Several well-established analysis methods, namely, statistical test, correlation analysis, and complex network analysis, were used to analyze the data. This study reports that symptom networks of patients with pediatric cough are related to the effectiveness of treatment: a dense network of symptoms is associated with great difficulty in treatment. Interventions with the most different symptoms in the symptom network may have improved therapeutic effects.
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Coronavirus disease 2019 (COVID-19) is now pandemic worldwide and has heavily overloaded hospitals in Wuhan City, China during the time between late January and February. We reported the clinical features and therapeutic characteristics of moderate COVID-19 cases in Wuhan that were treated via the integration of traditional Chinese medicine (TCM) and Western medicine. We collected electronic medical record (EMR) data, which included the full clinical profiles of patients, from a designated TCM hospital in Wuhan. The structured data of symptoms and drugs from admission notes were obtained through an information extraction process. Other key clinical entities were also confirmed and normalized to obtain information on the diagnosis, clinical treatments, laboratory tests, and outcomes of the patients. A total of 293 COVID-19 inpatient cases, including 207 moderate and 86 (29.3%) severe cases, were included in our research. Among these cases, 238 were discharged, 31 were transferred, and 24 (all severe cases) died in the hospital. Our COVID-19 cases involved elderly patients with advanced ages (57 years on average) and high comorbidity rates (61%). Our results reconfirmed several well-recognized risk factors, such as age, gender (male), and comorbidities, as well as provided novel laboratory indications (e.g., cholesterol) and TCM-specific phenotype markers (e.g., dull tongue) that were relevant to COVID-19 infections and prognosis. In addition to antiviral/antibiotics and standard supportive therapies, TCM herbal prescriptions incorporating 290 distinct herbs were used in 273 (93%) cases. The cases that received TCM treatment had lower death rates than those that did not receive TCM treatment (17/273 = 6.2% vs. 7/20= 35%, P = 0.0004 for all cases; 17/77= 22% vs. 7/9= 77.7%, P = 0.002 for severe cases). The TCM herbal prescriptions used for the treatment of COVID-19 infections mainly consisted of Pericarpium Citri Reticulatae, Radix Scutellariae, Rhizoma Pinellia, and their combinations, which reflected the practical TCM principles (e.g., clearing heat and dampening phlegm). Lastly, 59% of the patients received treatment, including antiviral, antibiotics, and Chinese patent medicine, before admission. This situation might have some effects on symptoms, such as fever and dry cough. By using EMR data, we described the clinical features and therapeutic characteristics of 293 COVID-19 cases treated via the integration of TCM herbal prescriptions and Western medicine. Clinical manifestations and treatments before admission and in the hospital were investigated. Our results preliminarily showed the potential effectiveness of TCM herbal prescriptions and their regularities in COVID-19 treatment.
الموضوعات
Adult , Aged , Aged, 80 and over , Female , Humans , Male , Middle Aged , COVID-19/therapy , China , Combined Modality Therapy , Drugs, Chinese Herbal/therapeutic use , Hospitalization , Medicine, Chinese Traditional , Retrospective Studies , Survival Rate , Treatment Outcomeالملخص
Acute ischemic stroke (AIS), as the third leading cause of death worldwide, is characterized by its high incidence, mortality rate, high incurred disability rate, and frequent reoccurrence. The neuroprotective effects of Ginkgo biloba extract (GBE) against several cerebral diseases have been reported in previous studies, but the underlying mechanisms of action are still unclear. Using a novel in vitro rat cortical capillary endothelial cell-astrocyte-neuron network model, we investigated the neuroprotective effects of GBE and one of its important constituents, Ginkgolide B (GB), against oxygen-glucose deprivation/reoxygenation and glucose (OGD/R) injury. In this model, rat cortical capillary endothelial cells, astrocytes, and neurons were cocultured so that they could be synchronously observed in the same system. Pretreatment with GBE or GB increased the neuron cell viability, ameliorated cell injury, and inhibited the cell apoptotic rate through Bax and Bcl-2 expression regulation after OGD/R injury. Furthermore, GBE or GB pretreatment enhanced the transendothelial electrical resistance of capillary endothelial monolayers, reduced the endothelial permeability coefficients for sodium fluorescein (Na-F), and increased the expression levels of tight junction proteins, namely, ZO-1 and occludin, in endothelial cells. Results demonstrated the preventive effects of GBE on neuronal cell death and enhancement of the function of brain capillary endothelial monolayers after OGD/R injury in vitro; thus, GBE could be used as an effective neuroprotective agent for AIS/reperfusion, with GB as one of its significant constituents.
الموضوعات
Animals , Rats , Apoptosis , Brain Ischemia , Drug Therapy , Cell Survival , Cells, Cultured , Disease Models, Animal , Endothelial Cells , Ginkgolides , Pharmacology , Glucose , Lactones , Pharmacology , Neurons , Neuroprotective Agents , Pharmacology , Oxygen , Plant Extracts , Pharmacology , Stroke , Drug Therapyالملخص
Determining effective traditional Chinese medicine (TCM) treatments for specific disease conditions or particular patient groups is a difficult issue that necessitates investigation because of the complicated personalized manifestations in real-world patients and the individualized combination therapies prescribed in clinical settings. In this study, a multistage analysis method that integrates propensity case matching, complex network analysis, and herb set enrichment analysis was proposed to identify effective herb prescriptions for particular diseases (e.g., insomnia). First, propensity case matching was applied to match clinical cases. Then, core network extraction and herb set enrichment were combined to detect core effective herb prescriptions. Effectiveness-based mutual information was used to detect strong herb-symptom relationships. This method was applied on a TCM clinical data set with 955 patients collected from well-designed observational studies. Results revealed that groups of herb prescriptions with higher effectiveness rates (76.9% vs. 42.8% for matched samples; 94.2% vs. 84.9% for all samples) compared with the original prescriptions were found. Particular patient groups with symptom manifestations were also identified to help investigate the indications of the effective herb prescriptions.
الموضوعات
Adolescent , Adult , Aged , Aged, 80 and over , Child , Female , Humans , Male , Middle Aged , Young Adult , Case-Control Studies , China , Drugs, Chinese Herbal , Therapeutic Uses , Medicine, Chinese Traditional , Propensity Score , Sleep Initiation and Maintenance Disorders , Drug Therapyالملخص
Clinical cases of TCM are used as important clinical data to record the whole process of the interaction between doctors and patients in the form of text.However,in the context of big data,there is a lack of research on the use of information covered in clinical cases.Therefore,we studied the method of extracting the symptom term from the history of present illness in TCM clinic in this paper,in order to lay the foundation for the further use of clinical cases.First,twelve thousand,three hundred and sixty-seven history data of present illness were obtained by random selection and expert review.According to the different disease types,they were divided into the two groups of the experiments:4,838 data in the diabetes group,7,529 data in the spleen and stomach disease group and 12,367 data in the mixed or combined group.A glossary of symptom terms covering 22,996 words were compiled.Then,five feature templates,such as sliding window feature,prefix and suffix character and lexical features,were selected.CRFs model was adopted to carry out named entity extraction experiment.As a result,in the open test,the performance of diabetes,spleen and stomach disease and mixed group were (0.83,0.8,0.82),(0.9,0.9,0.89) and (0.88,0.87,0.87),respectively,while the results were (0.83,0.82,0.83),(0.95,0.95,0.95) and (0.93,0.92,0.92) in the ten-fold cross validation.In conclusion,the results showed that the CRFs algorithm was an excellent sequence labeling algorithm and applied to the named entity extraction task of symptom history.
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Ontology alignment technology is a knowledge engineering method to realize the concept and relationship integration of different ontologies.In view of the same scope of ontology,such as disease ontology,developed by researchers from a number of different areas or institutions of independent research and development,there is a big difference between the term expression and the concept of the relationship.Thus,how to achieve the integration of multi-source ontology through alignment processing has been recognized as a significant methodological problem.In this paper,the concept,technology,method and corresponding tool of ontology alignment were expounded at full length.The technique of ontology alignment based on linguistic features and structural features was emphasized.Combined with the two international disease ontology:Disease Ontology and Orphanet,the experiment and analysis of the technique of ontology alignment were carried out and detailed the application of alignment technology.Furthermore,for the existing multi-source problems on TCM ontology database,the necessity and application of ontology alignment were discussed.
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How to discover the valuable knowledge from the large amount of prescription data accumulated in the long-term medical practice of traditional Chinese medicine (TCM) is one of the important contents of TCM modernization.Based on the prescription data of Xue' s clinical practice of many years,this paper explored the method of combining TCM network and prescription network to find out Xue' s common core drug combination.Based on 9,584 prescriptions in the Hospital Information System of Guang'anmen Hospital of China Academy of Chinese Medical Sciences,prescription network and drug network were constructed according to the similarity of prescription composition and drug co-occurrence relationship.Using the complex network analysis methods,such as community analysis method,to analyze the prescription and drug compatibility,the results were evaluated and analyzed by Xue and his successors.As a result,through complex network analysis,126 modular prescriptions and 4 TCM modules were obtained.One of the core components of the prescription module included Xiao Chai Hu decoction,Yin Qiao powder,and Sheng Jiang powder compound addition and subtraction.It was in consistent with the drug composition of exogenous febrile prescriptions excavated earlier.In conclusion,using the complex network methods,we can get some core drug combinations prescribed by Prof.Xue,and achieve the common compound core drug combination for treating diseases with certain vantages,laying a foundation for further inheriting and excavating Xue' s effective experience.
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Objective:To investigate the changes of occlusal plane in the process of retracting maxillary anterior teeth with different vertical traction force.Methods:The three dimensional finite element model of maxillary anterior teeth en-masse retraction by micro-implant was constructed with cone beam CT scanning and MIMICS and ANSYS software.Then the movement tendency of tooth and the changes of the maxillary occlusal plane was calculated when the vertical traction force was 0,0.5,0.75 and 1 N in the process of en-mass retraction,respectively.Results:Lingual tipping of anterior teeth,distal tipping of the first molar and the maxillary occlusal plane clockwise rotation by the retraction forces were observed.With the vertical traction force increasing,lingual tipping of anterior teeth and distal tipping of the first molar were decreased,and the occlusal plane clockwise rotation was prevented.Conclusion:The upper dentition movement and occlusal plane rotation can be changed effectively by the vertical traction with different force.When retract anterior teeth,0.5-0.75 N vertical traction force is beneficial to prevent clockwise rotation of the maxillary occlusal plane.
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Traditional Chinese medicine (TCM) clinical symptoms, which were main evidences in syndrome differentiation and treatment, were also main data in the clinical individual diagnosis and treatment. However, the absence of high-quality symptom ontology was still obvious in TCM clinical and data using. By analyzing the research and data of clinical phenotype ontologies associated with symptoms, this paper was aimed to introduce and sort the existing ontologies, in order to discuss related problems. Furthermore, we provided ideas and expound the importance of building data network of symptoms, diseases, genes, drugs, chemicals, side effects with the data we collected and disposed around symptoms, in order to construct TCM clinical phenotype ontology. We believed that our work will help the development of individual treatment and precision medicine in TCM. It was also the key of individual big data analysis which was urgent need to promote.
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Based on traditional Chinese medicine (TCM) herb data of inpatient department and senior famous TCM doctors from many TCM hospitals in China. Existing problems of TCM herb data standardization preprocessing were analyzed in order to explore scientific and reasonable preprocessing program which can provide technical support for the accurate analysis of herbal information. Clinical medicine doctors and herbal pharmacists collaborated and analyzed the real-world TCM herb data collected from multi-regions. In connection with characteristics of TCM, data mining was combined in the analysis of requirement to identify existing problems and explore appropriate problem-solving solutions. The results showed that based on the Pharmacopoeia of the People's Republic of China (PPRC, 2010 version) and regional herb preparing and dispensing guidelines, the herb collection rules, methods and processes were made for the herb data standardization. Herbal data processing program for different regions were formulated. It was concluded that herb data standardization rules and methods made by this plan solved standardization and accuracy of TCM herb data analysis and utilization in multi-area.
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Real world clinical diagnosis and treatment activity is a complicated decision-making task. The effective clinical cases of traditional Chinese medicine (TCM) of highly experienced physicians play an important role in the routine diagnosis and treatment and the formulation of medical knowledge . Based on TCM electronic medical record data, this paper proposed a decision support prototype system on TCM clinical diagnosis and treatment based on TCM effective clinical cases and case-based reasoning (CBR) algorithm, which is used to assist inexperienced clinicians to make more reliable clinical decisions, and thereafter to improve the clinical curative effectiveness. The system integrates TCM clinical cases data set from a TCM clinical data warehouse, and retrieves the similar cases based on CBR method. In particular, according to the underlying personalized diagnosis and treatment for patients in TCM, this system implemented a flexible diagnosis and treatment modification mechanism based on correlation analysis among symptoms, diagnoses (syndrome or pattern in TCM) and medicine. Finally, through a demonstration of clinical application, we made an initial evaluation of the usefulness and practical effects of the system.
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Due to the importance of molecular mechanisms of drug actions, network pharmacology has become a new perspective on drug mechanism research and novel drug discovery. Drug target prediction using computational methods, is one of the key research topics in network pharmacology. This paper reviewed the related research on drug target prediction methods. Furthermore, general principles of drug target prediction methods and key steps of them in recent years were summarized. Given the diversity of Chinese medicine ingredients, the network controlla-bility of herbs and the lack of high-quality pharmacological data, the network regulation mechanism of Chinese herb research will meet even more difficulties than modern drug research. Therefore, this paper also discussed main is-sues and research trends of Chinese herb target prediction. Finally, combining with the actual consolidated network data of Chinese herbs, chemical structure similarity computation and link prediction methods, the network-based herb target prediction method was proposed to demonstrate key research steps. Furthermore, we discussed the most significant research topics that we should addressed to enhance the high quality results of herb target prediction.
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Based on the Clinical Medical Research Information Sharing System ( CMRISS ) , this article took thedisease-syndrome-herb study on acute exacerbation of chronic obstructive pulmonary disease (AECOPD) as a model to explore the establishment of disease-syndrome-herb study method on many types of diseases for the guidance of Chinese medicine clinical practice. The CMRISS of the First Affiliated Hospital of Henan University of Traditional Chinese Medicine, which contained 5000 format electronic medical records from August 2011 to March 2013 , was used as the database . Data preprocessing , crystal reports and complex network were used in data mining to receive the frequency relation of AECOPD disease-syndrome-herb in order to analyze medica-tion features of different Chinese medicine clinical syndromes of AECOPD . The results showed that three syn-dromes, which were phlegm-heat obstructing the lungs, phlegm-stasis obstructing the lungs, and qi-yin deficien-cy, have corresponding Chinese herbs of licorice, orange peel and earthworm. The treatment of syndrome of phlegm-heat obstructing the lungs contains herbs to clear heat, remove phlegm and activate blood circulation. The treatment of syndrome of qi-yin deficiency contains herbs to benefitqi , nourish yin as well as to activate blood circulation and remove phlegm. It was concluded that the application of CMRISS is able to process a large amount of clinical data. The data mining results can be used to guide clinical practice. It provided a better plat-form for the scientific research of Chinese medicine clinical practice .
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This study was aimed to analyze correlation between traditional Chinese medicine (TCM) syndromes and symptoms of acute exacerbation chronic obstructive pulmonary disease (AECOPD) based on complex network in order to provide a scientific basis for TCM syndrome amendments of diagnostic criteria, and explore relevant technologies to promote its application. By way of the current Clinical Research Information Sharing System, data and data pro-cessing were carried out (EHR 3000 between August 2011 and January 2013) into the database by ETL software. The MISCR (correlation between common symptoms and common syndromes) from both common symptoms and com-mon syndromes of AECOPD was analyzed with existing diagnosis standards of AECOPD. The comparative analysis on TCM syndromes such as heat phlegm obstructing the lung, lung and kidney qi deficiency, phlegm turbid obstructing the lung and their correspondent existing diagnosis standards of AECOPD showed that the common TCM syndromes in the clinic are the mixture of deficiency and excess syndromes. However, some individual symptom is contradicted to its correspondent syndrome. It was concluded that based on the Clinical Research Information Sharing System, the research on correlation analysis between syndromes and symptoms of AECOPD can provide strong evidence and methodology for the validation and revision of TCM diagnostic criteria.
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To analyze the relationships among syndrome, therapeutic method and Chinese herbal medicine in patients with coronary artery disease (CAD).
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"Coming from clinical experiences and serving for the clinical application", which is the basic mode of academic development and technological progress of Chinese medicine. Clinical data embodies clinical experience and medical innovation and technology. Clinical data is also an important carrier to spread Chinese medicine and knowledge wealth for the whole country. The author thoroughly discussed the scientific value, necessity and significance of Chinese medicine clinical data in this article.
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To evaluate the clinical effects of Shengmai Injection in treating coronary heart disease (CHD) based on correct syndrome differentiation and incorrect syndrome differentiation.
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Objective Approaching characteristic of syndrome of type 2 diabetes mellitus affiliated metablic syndrome, usage of herbs based on the theories of relationship between formula (herbs) and syndrome. Methods Gathering 265 cases coming from multicentric clinic cases, feature of syndrome and classify would be approached by means of free-scale networks. Result Herbs of supplementing Qi and nourishing Yin is its foundation, effectiveness of herbs showed tendency in eliminating heat nourishing yin, then supplementing Qi and nourishing yin, eliminating heat, and invigorate vital energy promoting blood flow, warming yang, dissipating hygrosis for diuresis. Honey-fried radix astragal, pseudostellariae are important herbs, rehmannia dried rhizome, fructus schizandrae, chuanxiong, angelicae sinensis paeoniae rubra ophiopogonis tuber, anemarrhenae are correlation with them. Conclusion Deficiency of vital energy, Yin asthenia are fundamental syndrome of type 2 diabetes mellitus affiliated metablic syndrome. Early, Yin asthenia and excessive heat are cardinal. Intermediate stage, deficiency of vital energy Yin asthenia are fundamental. Meanwhile excessive heat, phlegmatic hygrosis and stagnated blood existed together. Advanced stage, deficiency of vital energy and stagnation of blood are main syndrome. Yang asthenia, phlegmatic hygrosis, retention of fluid in the body are affiliated syndrome frequently. Drug for invigorating blood circulation and eliminating stasis penetrated through the courses all the while.
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Objective:To analyze the experience of XU Peng-lin in using medicine in treating chronic gastritis,exploring the method for summarizing the experience of famous TCM practitioner.Methods:Professor Xu's 212 typical cases of chronic gastritis were collected,using related rules and point mutual information to analyze the prescription compatibility for the chronic gastritis.Results:Utilization of 12 kinds of drugs were over 30 percents,includinging Pinellia,dried ginger,mongolian milkvetch root,Medicinal Evodia Immature Fruit,and liquorice root,etc..The common compatibility rules were warming spleen-stomach to eliminat dampness,acridness and sweetness activating yang,sour-sweet herbs nourishing yin,pungency disperses while bitterness descends,application of both cold and heat,and combination of reinforcing and reducing.The basic prescriptions for chronic gastritis used by professor XU were Pinelliae Decoction for Purging Stomach-Fire,Zuojin Pill,Huangqi Jianzhong Decoction.Conclusion:Harmonizing yin and yang,reinforcing deficiency and reducing the excess,regulating the activities of qi,harmonizing zang and fu organs were the treatment for chronic gastritis by professor XU,which provided the methodological reference toTCM in treating the chronic gastritis.