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.

     

Incorporation of biological information in cancer risk assessment: Example — Vinyl chloride

Vinyl chloride (VC) is used as an example to demonstrate how biological information can be incorporated into quantitative risk assessment. The information included is the pharmacokinetics of VC in animals and humans and the data-generated hypothesis that VC primarily affects the initiation stage of the multistage carcinogenesis. The emphasis in this paper is on the improvement of risk assessment methodology rather than the risk assessment of VC per se.Sufficient data are available to construct physiologically-based pharmacokinetic models for both animals and humans. These models are used to calculate the metabolized dose corresponding to exposure scenarios in animals and in humans.On the basis of the data on liver angiosarcomas and carcinomas in rats, the cancer risk per unit of metabolized dose is comparable, irrespective of routes (oral or inhalation) of exposure. The tumor response from an intermittent/partial lifetime exposure is shown to be consistent with that from a lifetime exposure when VC is assumed to affect the first (initiation) stage of the multistage carcinogenic process. Furthermore, the risk estimates calculated on the basis of animal data are shown to be consistent with the human experience.     

Semiparametric Regression in Size-Biased Sampling

Summary .  Size-biased sampling arises when a positive-valued outcome variable is sampled with selection probability proportional to its size. In this article, we propose a semiparametric linear regression model to analyze size-biased outcomes. In our proposed model, the regression parameters of covariates are of major interest, while the distribution of random errors is unspecified. Under the proposed model, we discover that regression parameters are invariant regardless of size-biased sampling. Following this invariance property, we develop a simple estimation procedure for inferences. Our proposed methods are evaluated in simulation studies and applied to two real data analyses.     

Stress-induced consumption of ethanol by rats

The natural aversion of rats to ethanol was overcome by subjecting rats to immobilization stress for a two-week period during which increasing concentrations of ethanol were offered in the drinking water. The rats subjected to this regimen consumed 47% of total calories as ethanol, indefinitely, following removal of the stress. Ethanol was consumed at a rate of 17.1 g/kg body weight along with sufficient stock diet to assure adequate nutrition in the absence of ethanol.     

Dimeric chromenes and mixed dimers of a chromene with euparin from Encelia canescens

The investigation of Encelia canescens afforded, in addition to several known compounds, four new dimeric p-hydroxyacetophenone derivatives, two epimeric chromene dimers and two epimeric mixed dimers of euparin and encecalin. Furthermore, derivatives of tremetone and of encecalin were present. The structures were elucidated hy high field ¹H NMR spectroscopy.     

Use of ATP bioluminescence measurements for the estimation of biomass during biological humification

Summary The development of the microflora during the humification of grape pulp has been investigated by the determination of ATP using the bioluminescence technique. Several extraction methods were tested including the use of dimethylsulphoxide, trichloroacetic acid, grinding and ultrasonification. Dimethylsulphoxide and ultrasonification for 15 sec appeared to be the most effective. The ATP extract was stabilized when it was mixed with 0.75 mM glycine, 4.4 mM Mg-EDTA, pH 7.5 and frozen. The relative error of the ATP assay by bioluminescence did not exceed 6.5%. This method allowed us to show that at least five distinct reproducible microbial phases exist during grape pulp humification. These results show that the microbial biomass changes noticeably and at distinct times during composting.