Chewing lice from high‐altitude and migrating birds in Yunnan,China, with descriptions of two new species of Guimaraesiella

In total, 366 birds representing 55 species in 24 families and eight orders, were examined for chewing lice (Phthiraptera: Amblycera, Ischnocera) in two high‐altitude localities in Yunnan Province, China. In Ailaoshan, almost all of the birds examined were resident passeriforms, of which 36% were parasitized by chewing lice. In Jinshanyakou, most birds were on migration, and included both passerine and non‐passerine birds. Of the passerine birds caught in Jinshanyakou, only one bird (0.7%) was parasitized by chewing lice. The prevalence of Myrsidea and Brueelia‐complex lice on birds caught in Ailaoshan was higher than in previous reports. Of the chewing lice identifiable to species level, three represent new records for China: Actornithophilus hoplopteri (Mjöberg, 1910), Maculinirmus ljosalfar Gustafsson & Bush, 2017 and Quadraceps sinensis Timmermann, 1954. In total, 17 new host records are included, of which we describe two as new species in the Brueelia‐complex: Guimaraesiella (Cicchinella) ailaoshanensis sp. nov. ex Schoeniparus dubius dubius (Hume, 1874) and G. (C.) montisodalis sp. nov. ex Fulvetta manipurensis tonkinensis Delacour & Jabouille, 1930. This published work has been registered in ZooBank, http://zoobank.org/urn:lsid:zoobank.org:pub:9FC3D8EE‐2CED‐4DBE‐A1DB‐471B71260D27 .     

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.

     

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.     

Measurement of 7-dehydrocholesterol and cholesterol in hair can be used in the diagnosis of Smith-Lemli-Opitz syndrome

7-dehydrocholesterol (7-DHC) and cholesterol (CHOL) are biomarkers of Smith-Lemli-Opitz Syndrome (SLOS), a congenital autosomal recessive disorder characterized by elevated 7-DHC level in patients. Hair samples have been shown to have great diagnostic and research value, which has long been neglected in the SLOS field. In this study, we sought to investigate the feasibility of using hair for SLOS diagnosis. In the presence of antioxidants (2,6-ditert-butyl-4-methylphenol and triphenylphosphine), hair samples were completely pulverized and extracted by micro-pulverized extraction in alkaline solution or in n-hexane. After microwave-assisted derivatization with N,O-Bis(trimethylsilyl)trifluoroacetamide, the analytes were measured by GC-MS. We found that the limits of determination for 7-DHC and CHOL were 10 ng/mg and 8 ng/mg, respectively. In addition, good linearity was obtained in the range of 50–4000 ng/mg and 30–6000 ng/mg for 7-DHC and CHOL, respectively, which fully meets the requirement for SLOS diagnosis and related research. Finally, by applying the proposed method to real hair samples collected from 14 healthy infants and two suspected SLOS patients, we confirmed the feasibility of hair analysis as a diagnostic tool for SLOS. In conclusion, we present an optimized and validated analytical method for the simultaneous determination of two SLOS biomarkers using human hair.