Wnt-7a in feather morphogenesis: involvement of anterior-posterior asymmetry and proximal-distal elongation demonstrated with an in vitro reconstitution model.

How do vertebrate epithelial appendages form from the flat epithelia? Following the formation of feather placodes, the previously radially symmetrical primordia become anterior-posterior (A-P) asymmetrical and develop a proximo-distal (P-D) axis. Analysis of the molecular heterogeneity revealed a surprising parallel of molecular profiles in the A-P feather buds and the ventral-dorsal (V-D) Drosophila appendage imaginal discs. The functional significance was tested with an in vitro feather reconstitution model. Wnt-7a expression initiated all over the feather tract epithelium, intensifying as it became restricted first to the primordia domain, then to an accentuated ring pattern within the primordia border, and finally to the posterior bud. In contrast, sonic hedgehog expression was induced later as a dot within the primordia. RCAS was used to overexpress Wnt-7a in reconstituted feather explants derived from stage 29 dorsal skin to further test its function in feather formation. Control skin formed normal elongated, slender buds with A-P orientation, but Wnt-7a overexpression led to plateau-like skin appendages lacking an A-P axis. Feathers in the Wnt-7a overexpressing skin also had inhibited elongation of the P-D axes. This was not due to a lack of cell proliferation, which actually was increased although randomly distributed. While morphogenesis was perturbed, differentiation proceeded as indicated by the formation of barb ridges. Wnt-7a buds have reduced expression of anterior (Tenascin) bud markers. Middle (Notch-1) and posterior bud markers including Delta-1 and Serrate-1 were diffusely expressed. The results showed that ectopic Wnt-7a expression enhanced properties characteristic of the middle and posterior feather buds and suggest that P-D elongation of vertebrate skin appendages requires balanced interactions between the anterior and posterior buds.     

Growth-related expression of a double-stranded RNA-dependent protein kinase in 3T3 cells

Cultured mouse 3T3-F442A and 3T3-C2 fibroblasts exhibit a transient double-stranded RNA (dsRNA)-dependent phosphorylation of a 67,000-dalton protein (67K) without prior treatment with interferon (IFN). This phosphoprotein is similar but not identical to the dsRNA-dependent eukaryotic initiation factor-2 (eIF-2) alpha protein kinase (dsI), which regulates protein synthesis in rabbit reticulocytes. We have studied the relationship between cell growth and phosphorylation of the 67K protein (designated 3T3-dsRNA-dependent eIF-2 alpha kinase). A low level of dsRNA-dependent phosphorylation of 3T3-dsI was detectable in extracts prepared from cells not treated with IFN and grown at a low cell density. The phosphorylation of dsI and the phosphorylation of a 38K protein identified as the alpha-subunit (38K) of 3T3-eIF-2 (eIF-2 alpha) occurred concomitantly; the levels of these phosphorylations confluent and thereafter decreased markedly. Treatment of cells with IFN at all stages of growth resulted in an increase in phosphorylation of dsI. 3T3-F442A and 3T3-C2 fibroblasts were found to produce and secrete IFN at levels sufficient to induce an elevated dsI activity.     

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.     

A new species of Galearis (Orchidinae: Orchidaceae) from Sichuan,China

A new species, Galearis huanglongensis Q.W.Meng & Y.B.Luo, is described and illustrated. It is similar to Galearis cyclochila (Franch. & Sav.) Soó and Galearis diantha (Schltr.) P.F.Hunt, but differs in having a short spur, two elliptical lateral stigma lobes and distinctly separated bursicles. This new species is known only from the type locality, the Huanglong Valley, Songpan County, western Sichuan, China, growing amongst mosses under alpine shrubs at an elevation of about 3000 m. Based on two years of observations of its population size, the species was categorized as critically endangered CR (B1a, B2a) according to the World Conservation Union (IUCN) Red List Categories and Criteria, Version 3.1. The micromorphology of pollinia and seeds was observed by scanning electron microscopy and compared with that of G. cyclochila and G. diantha. The results supported G. huanglongensis Q.W.Meng & Y.B.Luo as a new species. © 2008 The Linnean Society of London, Botanical Journal of the Linnean Society, 2008, 158 , 689–695.     

Spatial and temporal factors associated with nest survival of Gray Flycatchers in managed ponderosa pine forests

Gray Flycatchers (Empidonax wrightii) breed in a variety of habitats in the arid and semi‐arid regions of the western United States, but little is known about their breeding biology, especially in the northern portion of their range where they nest in ponderosa pine (Pinus ponderosa) forests. From May to July 2014 and 2015, we conducted surveys for singing male Gray Flycatchers along the eastern slope of the Cascade Range in Washington, U.S.A, monitored flycatcher nests, and quantified nest‐site vegetation. We used a logistic‐exposure model fit within a Bayesian framework to model the daily survival probability of flycatcher nests. During the 2 yr of our study, we monitored 141 nests, with 93% in ponderosa pines. Mean clutch size was 3.6 eggs and the mean number of young fledged per nest was 3.2. Predation accounted for 90% of failed nests. We found a positive association between daily nest survival and both nest height and distance of nest substrates from the nearest tree. Flycatchers that locate their nests higher above the ground and further from adjacent trees may be choosing the safest alternative because higher nests may be less exposed to terrestrial predators and nests in trees that are farther from other trees may be less exposed to arboreal predators such as jays (Corvidae) that may forage in patches with connected canopies. Nests in trees farther from other trees may also allow earlier detection of approaching predators and thus aid in nest defense.