Objective To observe the effects of different posture on hemodynamics and plasma atrial natriuretic polypeptide(ANP) during laparoscopic surgery. Methods Forty patients who scheduled for elective laparoscopic surgery under general anesthesia were allocated into two groups according to their posture during laparoscopic surgery,20 cases for each group. In group A, the patients were arranged in a head-down tilt position, in group B, the patients were arranged in a head-up tilt position systolic blood pressure (SBP),diastolic blood pressure (DBP),central venous pressure (CVP) and electro cardio gram (ECC) were monitored continuously. Blood samples were taken from central venous at four time points of prepneumoperitoneum(T1), 10 minutes after that(T2) and 20 mintues(T3) when the patients were arranged at the different operation-needed position with a stable pneumoperitoneum pressure of 14 mm Hg (1 mm Hg = 0.133 kPa),and at 5 minutes (T4) after deflation of pneumoperitoneum when the patients returned to supine position. The plasma ANP was assessed by radioimmunoassay. Results In group A,the CVP at T2 and T3 [(14.45 ±2.72),(14.20 ±2.46) mm Hg] was significantly higher than that at T1 [(6.05 ±1.76) mm Hg] (P<0.01), in group B,the CVP at T2 and T3 [(8.90±1.27),(9.02 ±0.47) mm Hg] was significantly higher than that at T1[(6.30 ±1.34) mm Hg](P< 0.01) ,with a higher level in group A than those in group B at the same time point during pneumoperitoneum(P< 0.01). The ANP level in group A was higher at T2 than that at T1, and there was significantly higher at T3 than that at T1 (P < 0.05). But the ANP level was significantly higher in group A than that in group B at the same time points of T2 and T3 (P < 0.05). Conclusion The posture may have obvious effect on CVP and plasma ANP level during laparoscopic surgery.

To evaluate the feasibility of using human embryonic fibroblast(HEF) as feeder layer in the culture of human embryonic stem(ES) cells in vitro, we investigated the morphology, the sensitivity to 0.25% trypsin, the growth curve and cell cycle of HEF with DMEM(low glucose) +10% FBS used as culture medium, and then we compared HEF with mouse embryonic fibroblast (MEF). The results showed that both HEF and MEF are adherent cells in vitro, and HEF has longer life span and better growth ability than MEF. In room temperature, HEF is more sensitive to 0.25% trypsin. Our research suggested that HEF can be used as feeder layer in culture of ES cells. HEF has longer service life than MEF and is worthy to be studied further.
Animals ; Cell Cycle ; Cell Differentiation ; Cell Division ; Cells, Cultured ; Embryo, Mammalian ; cytology ; Fibroblasts ; cytology ; physiology ; Humans ; Mice

At present the prediction method of epilepsy patients is very time-consuming and vulnerable to subjective factors, so this paper presented an automatic recognition method of epilepsy electroencephalogram (EEG) based on common spatial model (CSP) and support vector machine (SVM). In this method, the CSP algorithm for extracting spatial characteristics was applied to the detection of epileptic EEG signals. However, the algorithm did not consider the nonlinear dynamic characteristics of the signals and ignored the time-frequency information, so the complementary characteristics of standard deviation, entropy and wavelet packet energy were selected for the combination in the feature extraction stage. The classification process adopted a new double classification model based on SVM. First, the normal, interictal and ictal periods were divided into normal and paroxysmal periods (including interictal and ictal periods), and then the samples belonging to the paroxysmal periods were classified into interictal and ictal periods. Finally, three categories of recognition were realized. The experimental data came from the epilepsy study at the University of Bonn in Germany. The average recognition rate was 98.73% in the first category and 99.90% in the second category. The experimental results show that the introduction of spatial characteristics and double classification model can effectively solve the problem of low recognition rate between interictal and ictal periods in many literatures, and improve the identification efficiency of each period, so it provides an effective detecting means for the prediction of epilepsy.
Algorithms ; Electroencephalography ; Epilepsy/diagnosis* ; Humans ; Signal Processing, Computer-Assisted ; Support Vector Machine