Establishment and verification of preeclampsia risk assessment model / 中华疾病控制杂志

Objective To analyze the risk factors affecting pre-eclampsia, to establish a pre-eclampsia risk assessment model, and to assess the risk of pre-eclampsia early. Methods A face-to-face questionnaire survey was conducted for all women who gave birth in the Department of Obstetrics, the First Hospital of Shanxi Medical University from March 2012 to September 2016. A total of 10 319 qualified questionnaires were collected to exclude 9 623 cases of other hypertensive diseases related to pregnancy. A total of 70% of the subjects were randomly selected as training samples to analyze the influencing factors of pre-eclampsia, and a Logistic regression model was established. The remaining 30% of the objects are used as test samples to verify the effect of the model. Results Logistic regression model was established with training samples. Logit P=-2.517-0.696×Pre-pregnancy lean +0.200 ×Pre-pregnancy overweight +0.944×Pre-pregnancy obesity -1.995×Residential in city -0.409×Folic acid supplemented before pregnancy +1.323×Twin and multiple pregnancy +1.708× History of previous pregnancy hypertension. Homer-Lemeshow test P=0.377. Model AUC=0.767 (95%CI:0.747-0.786, P<0.001). Using the test sample to verify the model, the model sensitivity was 81.68%, the specificity was 75.05%, the positive likelihood ratio was 3.27, and the negative likelihood ratio was 0.24. The test sample model AUC = 0.771 (95%CI=0.763-0.790,P<0.001). Conclusion This study establishes a simple and effective pre-eclampsia risk assessment model with controllable factors. The model has good fit and sensitivity and specificity.

Comparing performance of C5.0 decision tree and radial basis function neural network for predicting hemorrhagic transformation in patients with acute ischemic stroke / 中华疾病控制杂志

@# Objective To compare performance of C5.0 decision tree models and radial basis function(RBF) neural network in predicting the risk of hemorrhagic transformation in acute ischemic stroke. Methods Patients with acute ischemic stroke admitted to hospital were enrolled. Hemorrhagic transformation group and non-hemorrhagic transformation group were divided according to whether hemorrhagic transformation occurred within 2 weeks after admission. Retrospectively collected patients’ case information. C5.0 decision tree models and RBF neural network model were established with the ratio of 7 :3 for training set and test set, and the prediction performance of the model was compared. Results A total of 460 patients’ case information were collected and divided in 314 training set samples and 146 test set samples. Accuracy rates of the C5.0 decision tree model were 96.5% and 80.1%, sensitivities were 98.1% and 82.6%, specificities were 94.8% and 77.9%, Kappa index were 0.93 and 0.60, and AUC were 0.97 and 0.80. Accuracy rates of the neural network model were 72.6% and 74.7%, sensitivities were 87.6% and 88.4%, specificities were 56.9% and 62.3%, Kappa index were 0.45 and 0.50, and AUCs were 0.72 and 0.75. In the training set, the prediction performance of the C5.0 decision tree model was superior to the RBF neural network model. However, there was no statistical difference in the test set.Conclusion C5.0 decision tree model is better than RBF neural network model in risk prediction.

Construction of the full length and N-terminal fragment of serum response factor over-expressing lentiviral plasmid and its impacts on cardiac stem cell differentiation / 临床与实验病理学杂志

Purpose To analyze the effects of full length and N-terminal fragment of serum response factor (SRF-Full and SRF-N) on TGF-β1-induced differentiation in c-Kit + cardiac stem cells (CSC).Methods Rat SRF-Full and SRF-N (1-254 aa) coding sequences were obtained from cDNA library and cloned into the linearized lentviral vector GV358 (Ubi-MCS3FLAG-SV40-EGFP-IRES-puromycin) to generate the recombinant vectors,and then positive clones were selected and sequenced after transducing the competent cells with recombinant vectors.The recombinant lentvirus were packaged through transfecting the HEK293T cells with SRF-Full,SRF-N overexpressing plasmids and viral packaging plasmids.Neonatal SD rat cKit + CSCs were isolated via magnetic activated cell sorting,and TGF-β1-induced differentiation in SRF-Full and SRF-N overexpression virus-infected CSCs was assessed by quantitative PCR.Results SRF-Full and SRF-N coding sequences were successfully obtained and properly cloned into the linearized GV358.The positive clones were selected and further confirmed by sequencing.With the help of packaging plasmids,the SRFFull and SRF-N overexpressing plasmids-transfected HEK293T cells successfully produced the lentiviral particles with the titer of 2 × 108 TU/mL,and the SRF-Full-Flag and SRF-N-Flag fusion protein were detected by Western blot in virus-infected HEK293T cells.Addition of TGF-β1 significantly induced upregulated mRNAs in cardiomyocyte markers (Nkx2.5,Gata4,cTnI) and smooth muscle cell marker (SM22α) but not the epithelia cell marker (vWF) in CSCs.Overexpression of SRF-Full facilitated TGF-β1-triggered cardiomyocyte differentiation.However,SRF-N exerted anti-differentiation effects in TGF-β1-treated cells.Conclusion The SRF-Full and SRF-N overexpressing recombinant lentiviral vectors are successfully constructed.SRF-Full facilitates while SRF-N suppresses TGF-β1-induced cardiomyocyte differentiation in c-Kit + CSCs.

Cystatin C and serum creatinine in estimating acute kidney injury of shock patients / 世界急诊医学杂志（英文）

BACKGROUND: Serum creatinine (SCr) is the most commonly used parameter to estimate renal function impairement, but there are some shortcomings. Many factors including age, gender, drug, diet, muscle mass and metabolic rate can influence SCr, leading to an inaccurate estimation of kidney impairment. Studies have shown that cystatin C (CysC) is not affected by factors such as muscle mass, age, gender, diet, inflammation or tumor. The present study was undertaken to compare the sensitivity of CysC and SCr in evaluating renal function impairment at early stage of shock. METHODS: Seventy-one patients aged 38.3±21.4 years, who had been treated at the Emergency Medicine Department of the First Affiliated Hospital, Sun Yat-sen University between February 2006 and June 2007, were studied. They were divided into groups A, B, C, and D according to the shock time. Serum sample was drawn from each patient at 1, 2, 3, 4 hours after shock to determine SCr and CysC. CysC and SCr were determined again at 72 hours and 7 days after shock. RESULTS: CysC increased earlier than SCr in the 71 patients, and CysC decreased slower than SCr when shock was corrected. CysC increased at 1 hour after shock. There was a negative correlationship between CysC, SCr and glomerular filtration rate (GFR), especially at early stage of shock. CONCLUSIONS: There is renal injury at early stage of shock. CysC is more sensitive than SCr in assessing renal function at the early stage of shock.