A cross-talk between epithelium and endothelium mediates human alveolar–capillary injury during SARS-CoV-2 infection

COVID-19, caused by SARS-CoV-2, is an acute and rapidly developing pandemic, which leads to a global health crisis. SARS-CoV-2 primarily attacks human alveoli and causes severe lung infection and damage. To better understand the molecular basis of this disease, we sought to characterize the responses of alveolar epithelium and its adjacent microvascular endothelium to viral infection under a co-culture system. SARS-CoV-2 infection caused massive virus replication and dramatic organelles remodeling in alveolar epithelial cells, alone. While, viral infection affected endothelial cells in an indirect manner, which was mediated by infected alveolar epithelium. Proteomics analysis and TEM examinations showed viral infection caused global proteomic modulations and marked ultrastructural changes in both epithelial cells and endothelial cells under the co-culture system. In particular, viral infection elicited global protein changes and structural reorganizations across many sub-cellular compartments in epithelial cells. Among the affected organelles, mitochondrion seems to be a primary target organelle. Besides, according to EM and proteomic results, we identified Daurisoline, a potent autophagy inhibitor, could inhibit virus replication effectively in host cells. Collectively, our study revealed an unrecognized cross-talk between epithelium and endothelium, which contributed to alveolar–capillary injury during SARS-CoV-2 infection. These new findings will expand our understanding of COVID-19 and may also be helpful for targeted drug development.Subject terms: Mechanisms of disease, Viral infection     

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.

     

Mass Collaboration in Earthquake Risk Management

The mechanism of mass collaboration in risk management was studied during the Sichuan earthquake under a Web-based “PeopleFinder” project, where information is contributed and shared among mass contributors. The case study is provided by a great earthquake that happened in Wenchuan County, Sichuan Province, of southwestern China at 2:28 p.m. on May 12, 2008. We witnessed and experienced the rescue and relief efforts for the great earthquake. In this article, two fundamental frameworks are developed to study the mechanism of mass collaboration. Mass collaboration is proven to be effective in a big public crisis such as the Sichuan earthquake.     

On the classification of Calligonum juochiangense and C. pumilum (Polygonaceae)

After observing specimens of Calligonum pumilum Losinsk. and C. juochiangense Y. X. Liou in both the field and in herbarium collections, it was found that the morphological characters of these two species are quite different, especially with respect of the twisted direction of fruit ribs, number of bristle rows along each rib, rigidity and degree of interweaving of bristles, as well as their geographic distribution. Therefore, it is concluded that C. pumilum and C. juochiangense should be accepted as two independent species.     

长滩果引种驯化研究

长滩果系罗汉果最佳品种。原产区分布于永福和临桂县交界400—600米山区,但不适应于低丘陵和平原地区,因而不能在低丘陵和平原地区推广。为了解决这个问题。采用了(1)选择湿润和半阴的生长环境;(2)采用适应性强的砧木;(3)促成栽培;(4)加强秋旱期的科学管理等措施并取得成功,试验结果表明长滩果产量和品质达到或略超过原产区水平。     

罗汉果组培苗的栽培研究

本文报道罗汉果组培苗的栽培研究结果,为罗汉果在生产上推广应用组培苗栽培,提供有效的技术措施。