Single-cell landscape of the ecosystem in early-relapse hepatocellular carcinoma

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Diversity of endophytic bacteria and fungi in seeds of Elymus nutans growing in four locations of Qinghai Tibet Plateau,China

Plant and Soil - Seeds are involved in the transmission of microorganisms from one plant generation to the next, acting as initial inoculum for the plant microbiome, therefore provide a key source...     

Correlation between bilayer destabilization and activity enhancement by diacylglycerols in reconstituted Ca-ATPase vesicles

Using the reconstituted Ca-ATPase vesicles as a model system, we demonstrated that the presence of 1,2-dioleoyl-sn-glycerol (diolein) in the membrane introduces a pronounced enhancement in the Ca-transport function of Ca-ATPase, while the 1,2-dipalmitoyl-sn-glycerol (dipalmitin) does not. We also found by both 31P NMR and freeze-fraction electron microscopy that diolein destabilized lipid bilayers to a greater extent than did dipalmitin. We conclude that the tendency of diacylglycerols to destabilize the phospholipid bilayer is related to their capacity to enhance the activity of the membrane calcium pump.     

A study on giant panda recognition based on images of a large proportion of captive pandas

1. As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image‐based panda face recognition method.
2. In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition. For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. To develop and evaluate the algorithm, the largest panda image dataset containing 6,441 images from 218 different pandas, which is 39.78% of captive pandas in the world, is established.
3. The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.
4. This study shows that panda faces can be used for panda recognition. It enables the use of the cameras installed in their habitat for monitoring their population and behavior. This noninvasive approach is much more cost‐effective than the approaches used in the previous panda surveys.

     

Repeated pre-training sleep restriction in adolescent rats impaired spatial performance

Sleep and Biological Rhythms - Chronic sleep deprivation (SD) is an overwhelming problem in young students. Firstly, we investigated whether different levels of pre-training SD had effects on...