A total of 27 patients receiving both spinal CT and MR for evaluation of back pain were identified for analysis. MR images and CT image were co-registered first, and the CT was used as ground truth for training a deep learning algorithm using MR images to generate synthetic CT. In this study, we implemented cycleGAN to generate these synthetic CT images from their corresponding MR slices. Five-fold cross validation was used to evaluate the performance of the trained model. Compared to the original images, the Mean Average Error was 27.63±11.51, and the Peak Signal-to Noise Ratio was 19.44±5.72.
Broodiness is an unfavorable trait associated with the cessation of egg laying. Studies have found that excessive granulosa cell apoptosis and autophagy occur during goose broodiness. Other studies have also confirmed that oxidative stress is an important cause of apoptosis and autophagy. However, whether oxidative stress occurs during goose broodiness and whether this oxidative stress causes apoptosis and autophagy have not been fully elucidated. In this study, we investigated the effects of oxidative stress on the autophagy and apoptosis of granulosa cells in broody geese. The results showed higher mRNA expression of genes related to antioxidative stress responses (GPX, SOD-1, SOD-2, COX-2, CAT and hsp70) in pre-broody and broody geese than in laying birds. In addition, increased levels of granulosa cell apoptosis and autophagy were observed in pre-broody geese than in laying geese. Additionally, granulosa cells treated with H2O2 exhibited increased apoptosis and autophagy in vitro, and these effects were responsible for goose granulosa cell death. Moreover, vitamin E treatment effectively protected granulosa cells from H2O2-induced oxidative stress by inhibiting ROS production. Correspondingly, granulosa cell apoptosis and autophagy were greatly alleviated by vitamin E treatment. Together, our results demonstrated serious oxidative stress and granulosa cell apoptosis and autophagy in broody geese, and oxidative stress promoted apoptosis and autophagy. Vitamin E alleviated the autophagy and apoptosis of granulosa cells by inhibiting oxidative stress.
Abstract This study developed and validated a deep learning network using baseline magnetic resonance imaging (MRI) to predict Ki-67 status in meningioma patients. A total of 1239 patients were retrospectively recruited from three hospitals between January 2010 and December 2023, forming training, internal validation, and two external validation cohorts. A representation learning framework was utilized for modeling, and performance was assessed against existing methods. Furthermore, Kaplan–Meier survival analysis was conducted to investigate whether the model could be used for tumor growth prediction. The model achieved superior results, with areas under the curve (AUCs) of 0.797 for internal testing and 0.808 for generalization, alongside 0.756 and 0.727 for 3- and 5-year tumor growth predictions, respectively. The prediction was significantly associated with the growth of asymptomatic small meningiomas. Overall, the model provides an effective tool for early prediction of Ki-67 and tumor volume growth, aiding in individualized patient management.
Abstract Precision geometry measurement of the complex cutting tools has a significant impact on the machinability of components in the industry. However, acquisition of high-quality images in machine vision is a challenging problem due to the large slope and complex geometry of the cutting tools. In view of the vital function of illumination, this paper proposed a method of optimal design for the LEDs array. First, the calculation model of irradiance distribution on the measurement plane is established and the properties of the reflected light from the surface of cutting tools is analysed based on the BRDF theory. Then, the optimal parameters are solved through the specific algorithm flow for the LED array design. Finally, a flexible LED light source is fabricated with the optimal parameters for different features of the cutting tools and used in the measurement. The measurement results show that the error of the optimized light source is less than 1 \(%\) , and compared with the off-the-shelf light, the measurement accuracy is improved by 9.5$%$ on average. Moreover, this method also presents the potential applied in other complex objects.
DNA digital data storage refers to the technique of storing digital information on synthetic DNA. This paper introduces the method of converting digital information into genetic code based on ternary data conversion method. The "end-to-end" gene storage model was proposed without the use of address bits, which enabling unlimited information storage. With the distributed model, the information is evenly distributed among a plurality of storage tubes. Each storage tube eliminates a certain amount of data according to the congruence misplacement, and each of the chains adds 8-bit error correction bits. As a result, even if the order is disrupted, the regular order of genes can be still recovered by comparing the points. The error rate can be controlled at the average of, and the highest is, which is robust and secure.
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