Objective To explore the effects of multiple intravenous tranexamic acid (Ⅳ-TXA) administrations after total knee arthroplasty (TKA) on fibrinolytic activity and inflammatory response in an enhanced recovery after surgery (ERAS) program and to assess the efficacy and safety of Ⅳ-TXA.Methods One hundred and forty-one severe knee osteoarthritis patients following primary unilateral TKA from January 2016 to April 2017 were investigated retrospectively.The patients were divided into following three groups based on the dosage of Ⅳ-TXA after surgery:40 patients received ≤3 g Ⅳ-TXA after surgery (group T1),50 patients received 4 g (group T2) and the other 51 patients received ≥5 g Ⅳ-TXA (group T3).The total blood loss (TBL),hidden blood loss (HBL),transfusion rate,maximum hemoglobin (Hb) drop,the incidence of intramuscular venous thrombosis,deep vein thrombosis (DVT) and pulmonary embolism (PE),fibrinolysis parameters [fibrin(-ogeu) degradation products (FDP),D-dimer],and inflammation markers [C-reactive protein (CRP),interleukin-6 (IL-6)] during perioperative period were evaluated.In addition,correlation analyses between the dosage of Ⅳ-TXA and fibrinolysis parameters and inflammation markers were conducted.Results The mean TBL,HBL and maximum Hb drop in group T2 (537.16±270.43 ml,431.36±271.99 ml,19.68± 10.68 g/L) and T3 (541.31±290.00 ml,439.94±290.71 ml,20.24±8.48 g/L) were lower than those in group T1 (748.22±394.34 ml,P=0.012,0.013;636.47±388.14 ml,P=0.011,0.015;25.88± 11.77 g/L,P=0.005,0.010,respectively).No patient needed transfusion in all groups.There was no statistically difference in the incidence of intramuscular venous thrombosis of lower limbs among three groups (P＞ 0.05).No episode of DVT or PE occurred in any group in two weeks after surgery.There were negative correlation between the dosage of Ⅳ-TXA and FDP at postoperative day 1 and day 3 (r=-0.191,P=0.025;r=-0.291,P=0.001) and D-dimer on postoperative day 3 (r=-0.176,P=0.048).Moreover,the CRP (r=-0.184,P=0.036) and IL-6 (r=-0.269,P=0.002) level in serum on postoperatire day 1 also showed a negative relationship with the dosage of Ⅳ-TXA after surgery.Conclusion The multiple Ⅳ-TXA (≥4 g) after surgery can further reduce the TBL,HBL and maximum Hb drop following primary TKA in ERAS program without increasing the risk of thrombotic events.Most importantly,the effect of anti-fibrinolysis will be enhanced and may have an anti-inflammatory effect with the dosage of Ⅳ-TXA increased.

Objective:To explore the application value of automated machine learning (autoML) model in predicting the risk of preeclampsia in the first trimester.Methods:From January 2017 to October 2020, 2 180 singleton pregnant women who were registered in Jinan Second Maternal and Child Health Hospital and underwent pregnancy examination at 12 weeks of gestation were selected. The pregnant women were divided into preeclampsia group (103 cases) and control group (2 077 cases) according to the occurrence of preeclampsia. The differences in clinical data and hematological indexes in the two groups were compared, and the correlation between each index and the risk of preeclampsia was analyzed too. All the pregnant women were randomly divided into training set and test set according to the ratio of 7∶3, and the autogluon autoML algorithm was used to build a variety of machine learning models, and training and cross-validation were performed in the training set to compare the accuracy of the different models. The importance of each index in the autoML model was analyzed, and the autoML model and the logistic regression model were used to predict the risk of preeclampsia in pregnant women in the test set respectively, and the receiver operating characteristic (ROC) curve was used to evaluate the prediction performance of the autoML and the logistic regression model.Results:The age, pre-pregnancy body mass index, body mass index at 12 weeks of gestation, waist circumference at 12 weeks of gestation, proportion of drinking history, high-sensitivity C-reactive protein (hs-CRP), triglyceride, low-density lipoprotein cholesterol (LDL-C), aspartate aminotransferase (AST), platelet distribution width (PDW), mean platelet volume, thyroid stimulating hormone (TSH) and β-human chorionic gonadotropin were all significantly higher than those in the control group (all P<0.05), and the free tri-iodothyronine (free T3), free thyroxine (free T4), placental growth factor (PIGF), soluble fms-like tyrosine kinase-1 (sFlt-1) and pregnancy-associated plasma protein-A (PAPP-A) were all significantly lower than those in the control group (all P<0.05). Correlation analysis showed that the correlation between pre-pregnancy body mass index, body mass index at 12 weeks gestation, waist circumference at 12 weeks gestation, hs-CRP, triacylglycerol, AST, TSH, free T3, free T4, β-HCG, PIGF, sFlt-1, PAPP-A and preeclampsia risk were obviously higher; but the correlation between each index were lower. A total of 18 models in 8 categories were constructed with the autoML model algorithm, and the neural network _L2 based on FastAI had the highest accuracy in the training set (0.963) and the validation set (0.971). The TSH, LDL-C, PDW, waist circumference at 12 weeks of gestation, sFlt-1, AST were more important in the model, while the free T4, total cholesterol, pregnancy times, drinking history, parity and family history of hypertension were less important indicators. The area under the ROC curve of the autoML model for predicting the risk of preeclampsia in the first trimester was significantly higher than that of the logistic regression model (0.984 vs 0.765, P=0.002), while there was no statistical difference in the prediction accuracy of the two prediction models in the training set ( P>0.05). The prediction accuracy and sensitivity of the autoML model in the test set were both significantly higher than those of the logistic regression model (99.54% vs 98.32%, 93.75% vs 75.00%, both P<0.05). Conclusions:Factors such as TSH, LDL-C, PDW, waist circumference, sFlt-1 and AST in the first trimester of pregnancy have a certain correlation with the risk of preeclampsia. The autoML model based on the indicators of the first trimester has a high predictive value for the risk of preeclampsia.

Objective: To detect and analyze the differential expression profile of long non-coding RNA (lncRNA) in aggressive periodontitis (AgP) and healthy gingival tissues, in order to explore the role of lncRNA in AgP. Methods: After the informed consents were obtained, gingival tissues from AgP patients (n=40) and healthy volunteers (n=40) were collected in Department of Periodontology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine (from Mar. 2012 to Aug. 2012) and Department of Periodontology, Hospital of Stomatology, Tianjin Medical University (from Oct. 2016 to Apr. 2017). The differential expression of lncRNA of tissues from AgP patients (n=20) and healthy volunteers (n=20) were examined via microarray assay. Bioinformatics was applied to analyze the expression data of lncRNA and correlative mRNA. Two lncRNAs (lncRNA-TNFRSF13C and lncRNA-API5) were chosen to verify the microarray results by using real time quantitative polymerase chain reaction (PCR) in the other gingival tissues. Results: Compared with the result of healthy gingival tissues, totally 8 632 lncRNAs were differentially expressed in tissues from AgP patients. From these data, 1 986 lncRNAs were significantly upregulated while 6 646 lncRNAs were downregulated, amongst which 48 lncRNAs were upregulated (>10 times) (P<0.05), 14 lncRNAs were downregulated (>10 times) (P<0.05). Furthermore, totally 5 519 correlative mRNAs were differentially expressed, amongst which 1 676 mRNAs were upregulated (≥2 times, P<0.05) and 3 843 mRNAs were downregulated≤0.5 (P<0.05). The selected lncRNA-TNFRSF13C and lncRNA-API5 were up-regulated in AgP (P<0.05), which confirmed the results of microarray. From bioinformatics, differential expression lncRNAs were in association with many signal pathways including toll-like receptor signaling pathway, cell cycle and apoptosis pathway, and tumor necrosis factor receptor superfamily pathway. Conclusions LncRNA may be involved in the pathogenesis of AgP through various pathways, which need to be further explored.