Notes

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Cholangiocarcinoma is a highly malignant tumor. It is not sensitive to radiotherapy and chemotherapy and has a poor prognosis. At present, there is no effective treatment. As a new method for treating cancer, magnetic fluid hyperthermia has been clinically applied to a variety of cancers in recent years. This article introduces it to the cholangiocarcinoma model and systematically studies the effect of magnetic fluid hyperthermia on cholangiocarcinoma. Starting from the theory of magnetic fluid heating, the electromagnetic and heat transfer models were constructed in the finite element simulation software COMSOL using the Pennes biological heat transfer equation. The Helmholtz coil was used as an alternating magnetic field generating device. The relationship between the magnetic fluid-related properties and the heating power was analyzed according to Rosensweig's theory. After the multiphysics coupling simulation was performed, the electromagnetic field and thermal field distribution in the hyperthermia region were obtained. The results showed that the magnetic field distribution in the treatment area was uniform, and the thermal field distribution met the requirements of hyperthermia. After the magnetic fluid injection, the cholangiocarcinoma tissue warmed up rapidly, and the temperature of tumor tissues could reach above 42 °C, but the surrounding healthy tissues did not heat up significantly. At the same time, it was verified that the large blood vessels around the bile duct, the overflow of the magnetic fluid, and the eddy current heat had little effect on thermotherapy. The results of this article can provide a reference for the clinical application of magnetic fluid hyperthermia for cholangiocarcinoma.The feasibility of ultrasound backscatter homodyned K model parametric imaging (termed homodyned K imaging) to monitor coagulation zone during microwave ablation was investigated. Two recent estimators for the homodyned K model parameter, RSK (the estimation method based on the signal-to-noise ratio, the skewness, and the kurtosis of the amplitude envelope of ultrasound) and XU (the estimation method based on the first moment of the intensity of ultrasound, X statistics and U statistics), were compared. Firstly, the ultrasound backscattered signals during the microwave ablation of porcine liver ex vivo were processed by the noise-assisted correlation algorithm, envelope detection, sliding window method, digital scan conversion and color mapping to obtain homodyned K imaging. Then 20 porcine livers' microwave ablation experiments ex vivo were used to evaluate the effect of homodyned K imaging in monitoring the coagulation zone. The results showed that the area under the receiver operating characteristic curve of the RSK method was 0.77 ± 0.06 (mean ± standard deviation), and that of the XU method was 0.83 ± 0.08 (mean ± standard deviation). The accuracy to monitor the coagulation zone was (86 ± 10)% (mean ± standard deviation) by the RSK method and (90 ± 8)% (mean ± standard deviation) by the XU method. Compared with the RSK method, the Bland-Altman consistency for the coagulation zone estimated by the XU method and that of actual porcine liver tissue was higher. The time for parameter estimation and imaging by the XU method was less than that by the RSK method. We conclude that ultrasound backscatter homodyned K imaging can be used to monitor coagulation zones during microwave ablation, and the XU method is better than the RSK method.Vision is an important way for human beings to interact with the outside world and obtain information. In order to research human visual behavior under different conditions, this paper uses a Gaussian mixture-hidden Markov model (GMM-HMM) to model the scanpath, and proposes a new model optimization method, time-shifting segmentation (TSS). Bortezomib manufacturer The TSS method can highlight the characteristics of the time dimension in the scanpath, improve the pattern recognition results, and enhance the stability of the model. In this paper, a linear discriminant analysis (LDA) method is used for multi-dimensional feature pattern recognition to evaluates the rationality and the accuracy of the proposed model. Four sets of comparative trials were carried out for the model evaluation. The first group applied the GMM-HMM to model the scanpath, and the average accuracy of the classification could reach 0.507, which is greater than the opportunity probability of three classification (0.333). The second set of trial applied TSS method, and the mean accuracy of classification was raised to 0.610. The third group combined GMM-HMM with TSS method, and the mean accuracy of classification reached 0.602, which was more stable than the second model. Finally, comparing the model analysis results with the saccade amplitude (SA) characteristics analysis results, the modeling analysis method is much better than the basic information analysis method. Via analyzing the characteristics of three types of tasks, the results show that the free viewing task have higher specificity value and a higher sensitivity to the cued object search task. In summary, the application of GMM-HMM model has a good performance in scanpath pattern recognition, and the introduction of TSS method can enhance the difference of scanpath characteristics. Especially for the recognition of the scanpath of search-type tasks, the model has better advantages. And it also provides a new solution for a single state eye movement sequence.Bacomics is a unified framework for the interactions of the brain and the outside world, integrating the subject, method, and application mode of brain-apparatus conversation. This article divides the brain-apparatus conversation modes from the perspective of biological and non-biological apparatus, including the brain-biological organ interaction (BAC-1), brain-external non-living equipment and environment interaction (BAC-2), and the fusion agents of these two interactions (BAC-3), and explains the ways and potential applications in different modes.Transcranial direct current stimulation (tDCS) is an emerging non-invasive brain stimulation technique. However, the rehabilitation effect of tDCS on stroke disease is unclear. In this paper, based on electroencephalogram (EEG) and complex network analysis methods, the effect of tDCS on brain function network of stroke patients during rehabilitation was investigated. The resting state EEG signals of 31 stroke rehabilitation patients were collected and divided into stimulation group (16 cases) and control group (15 cases). The Pearson correlation coefficients were calculated between the channels, brain functional network of two groups were constructed before and after stimulation, and five characteristic parameters were analyzed and compared such as node degree, clustering coefficient, characteristic path length, global efficiency, and small world attribute. The results showed that node degree, clustering coefficient, global efficiency, and small world attributes of brain functional network in the tDCS group were significantly increased, characteristic path length was significantly reduced, and the difference was statistically significant ( P less then 0.
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