AIM: To study the effects of hypertonic NaCl-NaAc on microcirculation in hemorrhage-shocked rats.METHODS: SD rats were randomized into three groups of 7 5% NaCl(hypertonic saline, HS),5% NaCl-3 5% NaAc(hypertonic sodium acetate, HSA) and 0 9% NaCl(normal saline, NS) 4 mL/kg HS,HSA or NS was given intravenously following hemorrhagic shock The microcirculation of spinotrapezius muscle was observed RESULTS: HS increased mean aortic pressure more significant than HSA Variables including arteriolar and venular diameter,velocity and volumetric flow rate and open capillaries were increased and erythrocyte aggregation was decreased in 5 min after resuscitation with both HS and HSA solutions 5 min later,variables were deteriorated in HS group After local treatment, arteriolar and venular diameters were dilated significantly in HSA group CONCLUSION:HSA had superior effects to HS in improving microcirculation of hemorrhage-shocked rats

Objective Aiming at the problems of many items and long time to fill in the Constitution in Chinese Medicine Questionnaire(CCMQ)when evaluating individual constitution,the research uses artificial intelligence technology to select attributes,and to help construct a short version of the CCMQ.Methods Analyzing the constitution data provided by the Physical Examination Department of Jiangsu Province Hospital of Traditional Chinese Medicine,there are specific target variables as the classification of constitution types.Feature selection of genetic algorithm,cross-validation and KNN classification algorithm are used as filters to select problems,and the effect is evaluated by problem subset size,KNN classification accuracy and filling time.Results The method selected a short version of the CCMQ with 31 problems,and the average classification accuracy in the model was 86.16%,and the time was improved by 47.7%.Conclusion The algorithm can effectively find a better problem subset,achieve dimensionality reduction and have certain accuracy,thus helping to simplify the CCMQ.

OBJECTIVE Taking Professor Zhou Zhongying's clinical cases of treating hyperthyroidism as the research object,this article explored the use of the TabNet model based on neural networks to discover the diagnosis and treatment rules of hyperthyroid-ism,providing a method reference for inheriting the academic thoughts of famous veteran traditional Chinese medicine practitioners and assisting clinical diagnosis and treatment.METHODS Based on the clinical diagnosis and treatment cases of hyperthyroidism of Pro-fessor Zhou Zhongying and his team,standardized and structured training data were constructed;algorithms based on attention mecha-nism and sparse feature selection mechanism were studied;a pathogenesis prediction model was constructed by inputting standardized clinical manifestations,standardized tongue and pulse conditions;core symptoms,pathogenesis and medication were analyzed,as well as the relationship between the three.RESULTS The trained prediction model was used to predict the 6 pathogenesis of liver stagna-tion,liver fire,phlegm fluid,kidney deficiency,yin deficiency,and blood stasis.Compared with multi-label classification models constructed by classic algorithms such as decision trees and random forests,this model had better classification and prediction indica-tors.Mining was carried out through the decision tree algorithm,and 6 core pathogenesis corresponding Chinese medicine groups were summarized:vinegar-baked Bupleurum chinense,prunella vulgaris,oyster,processed Carapax trionycis,Scrophularia ningpoensis,Asparagus cochinchinensis,Ophiopogon japonicus,etc.CONCLUSION Using the TabNet algorithm on clinical medical record data to build a pathogenesis prediction model based on clinical manifestations,tongue and pulse conditions can effectively predict the core pathogenesis,and then discover the connection between symptoms,pathogenesis and medication,providing methodological references for the inheritance of academic ideas of famous veteran traditional Chinese medicine practitioners and clinical auxiliary diagnosis and treatment decision-making.