Objective To investigate the effects of inhalation of different concentrations of carbon monoxide (CO) on brain death (BD)-induced lung injury in rats. Methods Thirty-two pathogen free adult male Wistar rats weighing 250-300 g were randomly divided into 4 groups ( n= 8 each): group Ⅰ sham operation (group S);group Ⅱ brain death (group BD) and group Ⅲ and Ⅳ BD + CO 0.025% and 0.050% (group C1, C2 ). The animals were anesthetized and tracheally intubated. Fogarty catheter was inserted into the skull. BD was induced by inflating the balloon slowly at 20 μl/min until apnea developed. The animals were then mechanically ventilated (VT 10 ml/kg, RR 50 bpm, PEEP 2 cm H2O) with 40% O2 in N2 . In group Ⅲ and Ⅳ CO 0.025% and 0.050%were added to the air mixture respectively. In group S the balloon was not inflated. BD was confirmed by apnea,dilated pupils and flat EEG. In group BD,C1 and C2, MAP was maintained at 80-120 mm Hg by norepinephrine infusion. The arterial blood gas analysis was performed before (baseline) and immediately after BD was confirmed (T1) and at 30, 60, 90 and 120 min (T2-5) of CO inhalation. The animals were then sacrificed. The plasma concentrations of IL-6 and TNF-α and the activity of myeloperoxidase (MPO) in the lungs were measured. The W/D lung weight ratio and lung injury score (LIS) were recorded. Results BD significantly decreased PaO2/FiO2, BE and pH while increased plasma IL-6 and TNF-α concentrations, MPO activity in the lungs, the W/D ratio and lung injury score as compared with group S. CO inhalation ameliorated the deleterious effects induced by BD. The antiinfiammatory effect of 0.050% CO was better than that of 0.025 % CO. Conclusion Inhalation of 0.025 % or 0.050% CO can ameliorate BD-induced lung injury in rats, but there is no significant difference in the efficacy.

Objective:To explore the clinical application value of fetal heart quantification (fetal HQ) in the analysis of 24-segment spherical index (SI) of fetal heart in normal second and third trimestries.Methods:In July 2019, sixty-five normal singletons with gestational age (GA) of 28(24, 31) weeks were examined by echocardiography in Sir Run Run Shaw Hospital. The global spherical index (GSI) of the heart was measured and the dynamic images of the standard four chamber view were collected. Twenty-four-segment SI of the left and right ventricles were measured by using the fetal HQ analysis system and the correlation between SI and gestational age was analyzed.Results:There were no significant correlations between GSI, SI of left and right ventricles and gestational age ( r s=-0.22-0.14, all P>0.05). The SI of the first segment of left ventricle was lower than those of the other 23 segments (all P<0.05). There were no significant differences of SI among the second to the eleventh segments of the left ventricle (all P>0.05). In the 13th to the 24th segments of the left ventricle, the closer to the apex of the heart, the greater the SI of the segment were noted (all P<0.05). For the right ventricle, the closer to the apex of the heart, the greater the SI of the 4th to the 24th segments were found (all P<0.05), and there were no significant differences in SI among the first to third segment( P>0.05). The success rate of fetal HQ software was 95.4%. Conclusions:The 24-segment SI of RV and LV provides a feasible and reliable quantitative method which allows for the assessment of fetal heart function from the four-chamber view.

The finite element method is a new method to study the mechanism of brain injury caused by blunt instruments. But it is not easy to be applied because of its technology barrier of time-consuming and strong professionalism. In this study, a rapid and quantitative evaluation method was investigated to analyze the craniocerebral injury induced by blunt sticks based on convolutional neural network and finite element method. The velocity curve of stick struck and the maximum principal strain of brain tissue (cerebrum, corpus callosum, cerebellum and brainstem) from the finite element simulation were used as the input and output parameters of the convolutional neural network The convolutional neural network was trained and optimized by using the 10-fold cross-validation method. The Mean Absolute Error (MAE), Mean Square Error (MSE), and Goodness of Fit ( R ²) of the finally selected convolutional neural network model for the prediction of the maximum principal strain of the cerebrum were 0.084, 0.014, and 0.92, respectively. The predicted results of the maximum principal strain of the corpus callosum were 0.062, 0.007, 0.90, respectively. The predicted results of the maximum principal strain of the cerebellum and brainstem were 0.075, 0.011, and 0.94, respectively. These results show that the research and development of the deep convolutional neural network can quickly and accurately assess the local brain injury caused by the sticks blow, and have important application value for understanding the quantitative evaluation and the brain injury caused by the sticks struck. At the same time, this technology improves the computational efficiency and can provide a basis reference for transforming the current acceleration-based brain injury research into a focus on local brain injury research.
Brain ; Brain Injuries ; Computer Simulation ; Finite Element Analysis ; Humans ; Neural Networks, Computer

Ferroptosis is a non-apoptotic regulated cell death caused by iron accumulation and subsequent lipid peroxidation. Currently, the therapeutic role of ferroptosis on cancer is gaining increasing interest. Baicalin an active component in