An Ex Vivo Aorta Culture Model to Study Vascular Cellular Senescence.

Animal studies on vascular aging pose a few limitations. One of the most important reasons for this is the absence of a fast and efficient model of vascular tissue aging. In this study, ex vivo aortic culture and Matrigel subcutaneous implantation are combined to develop a new model for studying vascular cellular senescence. Eight-week-old C57BL/6J mice are used to obtain aortas. Bleomycin is used to induce aortas senescence in vitro. Then, aortas are transplanted to the acceptor mice with Matrigel. Senescence is evaluated using western blotting, quantitative polymerase chain reaction, and senescence-associated beta-galactosidase activity. Inflammatory cytokines are detected using Luminex Liquid Suspension Chip. RNA levels are analyzed by transcriptome sequencing. The results revealed that vessels in the bleomycin group exhibited significant senescence than those in the control group that can be enhanced by stripping vessel adventitia. The levels of cytokines such as interleukin (IL-2, IL-1ß, and IL-6 increased significantly in the ex vivo model. Furthermore, transcriptome sequencing revealed 56 significantly differentially expressed genes (DEGs) in ex vivo model vessels compared with those in naturally aging aortas. In conclusion, this study introduces a cost-effective and time-saving vessel senescence model for vascular cellular senescence.

The impact of national culture, altruism, and risk preference on salaries: The case of the Major League Baseball.

Based on the longitudinal data of 30 Major League Baseball (MLB) teams over seasons from 2017 to 2020, we used random effect (RE) models to conduct regression analyses on the detailed data of pitchers and fielders. Cultural distance (CD) was measured in terms of Hofstede's cultural indicators and Global Preference Survey (GPS) data. The results showed that salary premiums for foreign MLB players existed and CD was significantly positively correlated with salaries. Further, the risk preference (/altruism) difference between foreign pitchers and American pitchers was significantly positively (/negatively) correlated with the salaries of foreign pitchers. Salary estimation data showed that the salary premium was nearly 20% for players from South Korea and Panama, the lowest (only 0.11%) for players from Australia, and only 6.13% for players from Dominican Republic (accounting for the largest proportion of foreign MLB players), indicating that the MLB's foreign player recruitment policy is correct.

Automated segmentation of craniopharyngioma on MR images using U-Net-based deep convolutional neural network.

OBJECTIVES: To develop a U-Net-based deep learning model for automated segmentation of craniopharyngioma. METHODS: A total number of 264 patients diagnosed with craniopharyngiomas were included in this research. Pre-treatment MRIs were collected, annotated, and used as ground truth to learn and evaluate the deep learning model. Thirty-eight patients from another institution were used for independently external testing. The proposed segmentation model was constructed based on a U-Net architecture. Dice similarity coefficients (DSCs), Hausdorff distance of 95% percentile (95HD), Jaccard value, true positive rate (TPR), and false positive rate (FPR) of each case were calculated. One-way ANOVA analysis was used to investigate if the model performance was associated with the radiological characteristics of tumors. RESULTS: The proposed model showed a good performance in segmentation with average DSCs of 0.840, Jaccard of 0.734, TPR of 0.820, FPR of 0.000, and 95HD of 3.669 mm. It performed feasibly in the independent external test set, with average DSCs of 0.816, Jaccard of 0.704, TPR of 0.765, FPR of 0.000, and 95HD of 4.201 mm. Also, one-way ANOVA suggested the performance was not statistically associated with radiological characteristics, including predominantly composition (p = 0.370), lobulated shape (p = 0.353), compressed or enclosed ICA (p = 0.809), and cavernous sinus invasion (p = 0.283). CONCLUSIONS: The proposed deep learning model shows promising results for the automated segmentation of craniopharyngioma. KEY POINTS: • The segmentation model based on U-Net showed good performance in segmentation of craniopharyngioma. • The proposed model showed good performance regardless of the radiological characteristics of craniopharyngioma. • The model achieved feasibility in the independent external dataset obtained from another center.

A Vehicle Recognition Algorithm Based on Deep Transfer Learning with a Multiple Feature Subspace Distribution.

Vehicle detection is a key component of environmental sensing systems for Intelligent Vehicles (IVs). The traditional shallow model and offline learning-based vehicle detection method are not able to satisfy the real-world challenges of environmental complexity and scene dynamics. Focusing on these problems, this work proposes a vehicle detection algorithm based on a multiple feature subspace distribution deep model with online transfer learning. Based on the multiple feature subspace distribution hypothesis, a deep model is established in which multiple Restricted Boltzmann Machines (RBMs) construct the lower layers and a Deep Belief Network (DBN) composes the superstructure. For this deep model, an unsupervised feature extraction method is applied, which is based on sparse constraints. Then, a transfer learning method with online sample generation is proposed based on the deep model. Finally, the entire classifier is retrained online with supervised learning. The experiment is actuated using the KITTI road image datasets. The performance of the proposed method is compared with many state-of-the-art methods and it is demonstrated that the proposed deep transfer learning-based algorithm outperformed existing state-of-the-art methods.

[Preparation of freeze-dried long-circulation oridonin liposomes and their pharmacokinetics in rats].

OBJECTIVE: To prepare freeze-dried long-circulation oridonin liposomes with optimized parameters. METHODS: Ethanol injection method followed by freeze-drying was used to prepare the liposomes. Sephadex column was used to purify liposomes. Effects of formulation factors on entrapment efficiency of long-circulation oridonin liposomes were studied. The particle size, distribution and in vitro release were determined. Pharmacokinetics of oridonin liposomes in rats was determined by HPLC and the pharmacokinetic parameters calculated by Kinetica(TM) software were compared with conventional oridonin liposomes and solution. RESULTS: The optimized lipid formulation for long-circulation liposomes was composed of soy lecithin, cholesterol and DSPE-PEG 2000 with a ratio of 1:0.5:1.8(w/w). The ratio of drug to lipid was 1:6. Freeze-drying protectant was a mixture of glucose and mannitol (3:1). The entrapment efficiency (EE) of long-circulation oridonin liposomes was about 65%. The particle size of liposomes after hydrolyzation was 164 nm with good DPI. The liposomes showed a sustained drug release in vitro. Intravenous injected oridonin fitted with two-compartment pharmacokinetic model. The MRT of long-circulation liposomes was 2 times and 6 times and AUC was about 2 times and 3 times of conventional liposomes and oridonin solution, respectively. CONCLUSION: Freeze-dried liposomes with high EE have been obtained by the proposed approach. This long-circulation liposomes extend oridonin half time and significantly increase AUC in rats.