Techniques that model microvascular hemodynamics have been developed for decades. While the physiological significance of pressure pulsatility is acknowledged, most of the microcirculatory models use steady flow approaches. To theoretically study the extent and transmission of pulsatility in microcirculation, dynamic models need to be developed. In this paper, we present a one-dimensional model to describe the dynamic behavior of microvascular blood flow. The model is applied to a microvascular network from a rat mesentery. Intravital microscopy was used to record the morphology and flow velocities in individual vessel segments, and boundaries are defined according to the experimental data. The system of governing equations constituting the model is solved numerically using the discontinuous Galerkin method. An implicit integration scheme is adopted to increase computing efficiency. The model allows the simulation of the dynamic properties of blood flow in microcirculatory networks, including the pressure pulsatility (quantified by a pulsatility index) and pulse wave velocity (PWV). From the main input arteriole to the main output venule, the pulsatility index decreases by 66.7%. PWV obtained along arterioles declines with decreasing diameters, with mean values of 77.16, 25.31, and 8.30 cm/s for diameters of 26.84, 17.46, and 13.33 μm, respectively. These results suggest that the 1D model developed is able to simulate the characteristics of pressure pulsatility and wave propagation in complex microvascular networks.
In intensive care unit (ICU), it is essential to predict the mortality of patients and mathematical models aid in improving the prognosis accuracy. Recently, recurrent neural network (RNN), especially long short-term memory (LSTM) network, showed advantages in sequential modeling and was promising for clinical prediction. However, ICU data are highly complex due to the diverse patterns of diseases; therefore, instead of single LSTM model, an ensemble algorithm of LSTM (eLSTM) is proposed, utilizing the superiority of the ensemble framework to handle the diversity of clinical data. The eLSTM algorithm was evaluated by the acknowledged database of ICU admissions Medical Information Mart for Intensive Care III (MIMIC-III). The investigation in total of 18415 cases shows that compared with clinical scoring systems SAPS II, SOFA, and APACHE II, random forests classification algorithm, and the single LSTM classifier, the eLSTM model achieved the superior performance with the largest value of area under the receiver operating characteristic curve (AUROC) of 0.8451 and the largest area under the precision-recall curve (AUPRC) of 0.4862. Furthermore, it offered an early prognosis of ICU patients. The results demonstrate that the eLSTM is capable of dynamically predicting the mortality of patients in complex clinical situations.
Jujuboside A (JuA) is a main component of jujubogenin extracted from the seed of Ziziphus jujuba Mill var spinosa (Bunge) Hu ex H F Chou (Ziziphus), which is widely used in Chinese traditional medicine for the treatment of insomnia and anxiety. Previously, we reported the inhibitory effects of JuA on hippocampal formation in vivo and in vitro, the present study was carried out to examine the effects of JuA on glutamate (Glu)-mediated excitatory signal pathway in hippocampus. Microdialysis coupled with high-performance liquid chromatography (HPLC) was used to monitor the changes of Glu levels in the hippocampus induced by penicillin sodium, or a mixture of penicillin sodium and JuA. The results showed that penicillin increased the hippocampal Glu concentration (p < 0.01) and a high dose of JuA (0.1 g/L) significantly blocked penicillin-induced Glu release (p < 0.05). Moreover, the effect of JuA on intracellular Ca2+ changes after the stimulation by Glu was studied in cultured hippocampal neurons with confocal laser scanning microscope (CLSM). It was found that Glu (0.5 mM) induced an intracellular [Ca2+]i increase (p < 0.01), and JuA significantly inhibited the Glu-induced Ca2+ increase. The calmodulin (CaM) antagonist trifluoperazine (TFP) showed a similar inhibitory effect as JuA. These observations suggested that JuA has inhibitory effects on Glu-mediated excitatory signal pathway in hippocampus and probably acts through its anti-calmodulin action.
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