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.     

Molecular Dynamics Simulations of PIP2 and PIP3 in Lipid Bilayers: Determination of Ring Orientation, and the Effects of Surface Roughness on a Poisson-Boltzmann Description

Molecular dynamics (MD) simulations of phosphatidylinositol (4,5)-bisphosphate (PIP₂) and phosphatidylinositol (3,4,5)-trisphosphate (PIP₃) in 1-palmitoyl 2-oleoyl phosphatidylcholine (POPC) bilayers indicate that the inositol rings are tilted ∼40° with respect to the bilayer surface, as compared with 17° for the P-N vector of POPC. Multiple minima were obtained for the ring twist (analogous to roll for an airplane). The phosphates at position 1 of PIP₂ and PIP₃ are within an Ångström of the plane formed by the phosphates of POPC; lipids in the surrounding shell are depressed by 0.5-0.8 Å, but otherwise the phosphoinositides do not substantially perturb the bilayer. Finite size artifacts for ion distributions are apparent for systems of ∼26 waters/lipid, but, based on simulations with a fourfold increase of the aqueous phase, the phosphoinositide positions and orientations do not show significant size effects. Electrostatic potentials evaluated from Poisson-Boltzmann (PB) calculations show a strong dependence of potential height and ring orientation, with the maxima on the −25 mV surfaces (17.1 ± 0.1 Å for PIP₂ and 19.4 ± 0.3 Å for PIP₃) occurring near the most populated orientations from MD. These surfaces are well above the background height of 10 Å estimated for negatively charged cell membranes, as would be expected for lipids involved in cellular signaling. PB calculations on microscopically flat bilayers yield similar maxima as the MD-based (microscopically rough) systems, but show less fine structure and do not clearly indicate the most probable regions. Electrostatic free energies of interaction with pentalysine are also similar for the rough and flat systems. These results support the utility of a rigid/flat bilayer model for PB-based studies of PIP₂ and PIP₃ as long as the orientations are judiciously chosen.     

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.     

Rapid high-performance liquid chromatographic determination of serum gabapentin

Gabapentin (GBP) is a new antiepileptic drug approved for clinical treatment of partial seizures in the USA. Serum GBP concentrations in 283 patients were studied using high-performance liquid chromatography with fluorescence detection. The standard curves were linear over a range of 60 ng to 15 μg/ml. The coefficient of variations were 3.4 to 8.8% and 1.4 to 9.8% for intra- and inter-assay studies, respectively. The lower limit of quantitation was 10 ng/ml. Of the 283 patients studied, 72.5% had GBP levels between 2 and 10 μg/ml, 14.8% were below 2 μg/ml and 12.7% above 10 μg/ml. The mean±S.E. of GBP in 283 patients was 5.38±0.23 μg/ml. Peak concentrations of more than 15 μg/ml and trough levels as low as 0.1 μg/ml were not uncommon. The method described was rapid, simple, highly sensitive and reproducible. Other antiepileptic drugs and endogenous compounds did not interfere with the assay.