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Atrioesophageal fistula pursuing ablation procedures with regard to atrial fibrillation: methodical overview of case accounts.
18 N and 497.28 N for z and resultant, respectively, and the rationality of the new musculoskeletal model was verified.The background of abdominal computed tomography (CT) images is complex, and kidney tumors have different shapes, sizes and unclear edges. Consequently, the segmentation methods applying to the whole CT images are often unable to effectively segment the kidney tumors. To solve these problems, this paper proposes a multi-scale network based on cascaded 3D U-Net and DeepLabV3+ for kidney tumor segmentation, which uses atrous convolution feature pyramid to adaptively control receptive field. Through the fusion of high-level and low-level features, the segmented edges of large tumors and the segmentation accuracies of small tumors are effectively improved. A total of 210 CT data published by Kits2019 were used for five-fold cross validation, and 30 CT volume data collected from Suzhou Science and Technology Town Hospital were independently tested by trained segmentation models. The results of five-fold cross validation experiments showed that the Dice coefficient, sensitivity and precision were 0.796 2 ± 0.274 1, 0.824 5 ± 0.276 3, and 0.805 1 ± 0.284 0, respectively. On the external test set, the Dice coefficient, sensitivity and precision were 0.817 2 ± 0.110 0, 0.829 6 ± 0.150 7, and 0.831 8 ± 0.116 8, respectively. The results show a great improvement in the segmentation accuracy compared with other semantic segmentation methods.This study explored the variation of bursting force of multi-chamber infusion bag with different geometry size, providing guidance for its optimal design. Models of single-chamber infusion bag with different size were established. The finite element based on fluid cavity method was adopted to calculate the fluid-solid coupling deformation process of infusion bag to obtain corresponding critical bursting force. As a result, we proposed an empirical formula predicting the critical bursting force of one chamber infusion bag with specified geometry size. Besides, a theoretical analysis, which determines the force condition of three chamber infusion bag when falling from high altitude, was conducted. The proportion of force loaded on different chamber was gained. The results indicated that critical bursting force is positively related to the length and width of the chamber, and negatively related to the height of the chamber. While the infusion bag falling, the impact force loaded on each chamber is proportional to the total liquid within it. To raise the critical bursting force of in fusion bag, a greater length and width corresponding to reduced height are recommended considering the volume of liquid needed to be filled in.Platelets are non-nucleated blood effector cells, which plays an important role in coagulation, hemostasis, and thrombosis. However, platelets are extremely susceptible to activation by external stimuli, which in turn damages the platelet's natural biological activity and affects its biological function. Platelet biological activity has become a hotspot in the field of vascular diseases. In this study, ultrasound parameters (ultrasound intensity and duration time) were used to intervene in the biological activity of platelets. The response of platelets to ultrasound energy was explored from the aspects of platelet morphology, aggregation ability and particle release (the expression of P-selectin and the number of particles). The results showed that the ultrasound intensity of 0.25 W/cm 2 (1 MHz, 60 s) had no effect on the morphology, aggregation ability and particle release of platelets. When the ultrasonic intensity was increased to greater than 0.25 W/cm 2, the generation of platelet pseudopods, morphological changes, increase of particle release, as well as effect on aggregation were observed. When the ultrasound duration time was 60 s (1 MHz, 0.25 W/cm 2), it had no effect on the biological activity of platelets. However, when the ultrasound time was greater than 60 s, the morphology, aggregation ability and microparticles release would been induced with no effect on the secretion of CD62P and total protein components. Therefore, when the ultrasound parameters were 1 MHz and 0.25 W/cm 2 with 60 s duration time, the ultrasound energy had no effect on the biological activity of platelets. The results in this study are of great significant for ultrasound energy intervention for the treatment of platelet-related diseases.The temperature dependence of relative permittivity and conductivity of ex-vivo pig liver, lung and heart at 2 450 MHz was studied. The relative permittivity and conductivity of three kinds of biological tissues were measured by the open-end coaxial line method. The dielectric model was fitted according to the principle of least square method. The results showed that the relative permittivity and conductivity of pig liver, pig lung and pig heart decreased with the increase of tissue temperature from 20 to 80 ℃. The relative permittivity and conductivity models of pig liver, pig lung and pig heart were established to reflect the law of dielectric properties of biological tissue changing with temperature and provide a reference for the parameters setting of thermal ablation temperature field.Patch clamp is a technique that can measure weak current in the level of picoampere (pA). It has been widely used for cellular electrophysiological recording in fundamental medical researches, such as membrane potential and ion channel currents recording, etc. In order to obtain accurate measurement results, both the resistance and capacitance of the pipette are required to be compensated. Capacitance compensations are composed of slow and fast capacitance compensation. The slow compensation is determined by the lipid bilayer of cell membrane, and its magnitude usually ranges from a few picofarads (pF) to a few microfarads (μF), depending on the cell size. The fast capacitance is formed by the distributed capacitance of the glass pipette, wires and solution, mostly ranging in a few picofarads. After the pipette sucks the cells in the solution, the positions of the glass pipette and wire have been determined, and only taking once compensation for slow and fast capacitance will meet the recording requirements. However, when the study needs to deal with the temperature characteristics, it is still necessary to make a recognition on the temperature characteristic of the capacitance. We found that the time constant of fast capacitance discharge changed with increasing temperature of bath solution when we studied the photothermal effect on cell membrane by patch clamp. Based on this phenomenon, we proposed an equivalent circuit to calculate the temperature-dependent parameters. Experimental results showed that the fast capacitance increased in a positive rate of 0.04 pF/℃, while the pipette resistance decreased. The fine data analysis demonstrated that the temperature rises of bath solution determined the kinetics of the fast capacitance mainly by changing the inner solution resistance of the glass pipette. This result will provide a good reference for the fine temperature characteristic study related to cellular electrophysiology based on patch clamp technique.Atrial fibrillation (AF) is a common arrhythmia, which can lead to thrombosis and increase the risk of a stroke or even death. In order to meet the need for a low false-negative rate (FNR) of the screening test in clinical application, a convolutional neural network with a low false-negative rate (LFNR-CNN) was proposed. Regularization coefficients were added to the cross-entropy loss function which could make the cost of positive and negative samples different, and the penalty for false negatives could be increased during network training. The inter-patient clinical database of 21 077 patients (CD-21077) collected from the large general hospital was used to verify the effectiveness of the proposed method. For the convolutional neural network (CNN) with the same structure, the improved loss function could reduce the FNR from 2.22% to 0.97% compared with the traditional cross-entropy loss function. The selected regularization coefficient could increase the sensitivity (SE) from 97.78% to 98.35%, and the accuracy (ACC) was 96.62%, which was an increase from 96.49%. The proposed algorithm can reduce the FNR without losing ACC, and reduce the possibility of missed diagnosis to avoid missing the best treatment period. Meanwhile, it provides a universal loss function for the clinical auxiliary diagnosis of other diseases.Sleep apnea (SA) detection method based on traditional machine learning needs a lot of efforts in feature engineering and classifier design. We constructed a one-dimensional convolutional neural network (CNN) model, which consists in four convolution layers, four pooling layers, two full connection layers and one classification layer. The automatic feature extraction and classification were realized by the structure of the proposed CNN model. The model was verified by the whole night single-channel sleep electrocardiogram (ECG) signals of 70 subjects from the Apnea-ECG dataset. Our results showed that the accuracy of per-segment SA detection was ranged from 80.1% to 88.0%, using the input signals of single-channel ECG signal, RR interval (RRI) sequence, R peak sequence and RRI sequence + R peak sequence respectively. These results indicated that the proposed CNN model was effective and can automatically extract and classify features from the original single-channel ECG signal or its derived signal RRI and R peak sequence. When the input signals were RRI sequence + R peak sequence, the CNN model achieved the best performance. The accuracy, sensitivity and specificity of per-segment SA detection were 88.0%, 85.1% and 89.9%, respectively. And the accuracy of per-recording SA diagnosis was 100%. These findings indicated that the proposed method can effectively improve the accuracy and robustness of SA detection and outperform the methods reported in recent years. The proposed CNN model can be applied to portable screening diagnosis equipment for SA with remote server.Mental fatigue is the subjective state of people after excessive consumption of information resources. Its impact on cognitive activities is mainly manifested as decreased alertness, poor memory and inattention, which is highly related to the performance after impaired working memory. In this paper, the partial directional coherence method was used to calculate the coherence coefficient of scalp electroencephalogram (EEG) of each electrode. The analysis of brain network and its attribute parameters was used to explore the changes of information resource allocation of working memory under mental fatigue. Mental fatigue was quickly induced by the experimental paradigm of adaptive N-back working memory. Twenty-five healthy college students were randomly recruited as subjects, including 14 males and 11 females, aged from 20 to 27 years old, all right-handed. The behavioral data and resting scalp EEG data were collected simultaneously. The results showed that the main information transmission pathway of the brain changed under mental fatigue, mainly in the frontal lobe and parietal lobe. The significant changes in brain network parameters indicated that the information transmission path of the brain decreased and the efficiency of information transmission decreased significantly. In the causal flow of each electrode and the information flow of each brain region, the inflow of information resources in the frontal lobe decreased under mental fatigue. Although the parietal lobe region and occipital lobe region became the main functional connection areas in the fatigue state, the inflow of information resources in these two regions was still reduced as a whole. Selleck FDA-approved Drug Library These results indicated that mental fatigue affected the information resources allocation of working memory, especially in the frontal and parietal regions which were closely related to working memory.
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