Low temperature alleviated the adverse effects of simulated transport stress on the intestinal health in Chinese soft-shelled turtle Pelodiscus sinensis.

Transport stress always poses a threat to aquatic animals. Transportation under low temperatures was often used to relieve transport stress in practical production of Chinese soft-shelled turtle Pelodiscus sinensis, but their effect on the turtle's intestinal barrier remains unclear. In this study, P. sinensis (initial weight 200 ± 20 g) were exposed to simulated transport stress for 12 h at control (30 °C) and low (20 °C) temperature, and then recovery for 24 h, and each treatment had 4 replicates with each replicate containing 4 turtles. The results showed that transportation induced obvious morphological and histological damages in intestinal villus, with a down-regulated expression of the tight junction related genes. Besides turtles in transport group showed an oxidative stress in intestine, which stimulated a physiological detoxification response together with apoptosis. Low temperature transport plays a mitigative effect on the transport stress of turtle intestine via relieved stress response. Specifically, the intestinal villus/crypt (V/C) ratio and the expression of tight junction genes in the low-temperature group were significantly higher compared to the control temperature group, while stress response parameters such as intestinal cortisol levels and hsp expression were significantly lower in the low-temperature group. Additionally, low temperature alleviated oxidative damage and apoptosis caused by transport stress relative to the control temperature group. However, the protective effect of low temperature on P. sinensis intestine was limited, especially after the temperature recovery stage. Overall, the findings of the present study demonstrated that transport stress would induce the disruption of intestinal integrity and oxidative damage, also activated the mucosal immunity and antioxidant enzyme system response of turtles. It was also suggested that low temperature could alleviate the adverse effects of transport stress on intestinal integrity through modulation of oxidative status and apoptosis, whereas much less impact after temperature recovery.

Multi-Person Pose Regression With Distribution-Aware Single-Stage Models.

Understanding human posture is a challenging topic, which encompasses several tasks, e.g., pose estimation, body mesh recovery and pose tracking. In this article, we propose a novel Distribution-Aware Single-stage (DAS) model for the pose-related tasks. The proposed DAS model estimates human position and localizes joints simultaneously, which requires only a single pass. Meanwhile, we utilize normalizing flow to enable DAS to learn the true distribution of joint locations, rather than making simple Gaussian or Laplacian assumptions. This provides a pivotal prior and greatly boosts the accuracy of regression-based methods, thus making DAS achieve comparable performance to the volumetric-based methods. We also introduce a recursively update strategy to progressively approach the regression target, reducing the difficulty of regression and improving the regression performance. We further adapt DAS to multi-person mesh recovery and pose tracking tasks and achieve considerable performance on both tasks. Comprehensive experiments on CMU Panoptic and MuPoTS-3D demonstrate the superior efficiency of DAS, specifically 1.5 times speedup over previous best method, and its state-of-the-art accuracy for multi-person pose estimation. Extensive experiments on 3DPW and PoseTrack2018 indicate the effectiveness and efficiency of DAS for human body mesh recovery and pose tracking, respectively, which prove the generality of our proposed DAS model.