Complete Genome Sequence of Hepatitis E Virus from Rabbits in the United States

Hepatitis E virus (HEV) is a single-strand positive-sense RNA virus in the family Hepeviridae. The disease caused by HEV, hepatitis E, is an important public health problem in developing countries of Asia and Africa and is also endemic in many industrialized countries, including the United States. HEV has been identified from several other animal species in addition to humans, including the pig, chicken, mongoose, deer, rabbit, ferret, bat, and fish. Here we report the complete genome sequence of the first strain of HEV from rabbits in the United States. Sequence and phylogenetic analyses revealed that the U.S. rabbit HEV is a distant member of the zoonotic genotype 3 HEV, thus raising a concern for potential zoonotic human infection. A unique 90-nucleotide insertion within the X domain of the ORF1 was identified in the rabbit HEV, and this insertion may play a role in the species tropism of HEV.     

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.     

Modulatory effect of Lactobacillus acidophilus KLDS 1.0738 on intestinal short‐chain fatty acids metabolism and GPR41/43 expression in β‐lactoglobulin–sensitized mice

We investigated the correlation between the beneficial effect of Lactobacillus acidophilus on gut microbiota composition, metabolic activities, and reducing cow's milk protein allergy. Mice sensitized with β‐lactoglobulin (β‐Lg) were treated with different doses of L. acidophilus KLDS 1.0738 for 4 weeks, starting 1 week before allergen induction. The results showed that intake of L. acidophilus significantly suppressed the hypersensitivity responses, together with increased fecal microbiota diversity and short‐chain fatty acids (SCFAs) concentration (including propionate, butyrate, isobutyrate, and isovalerate) when compared with the allergic group. Moreover, treatment with L. acidophilus induced the expression of SCFAs receptors, G‐protein–coupled receptors 41 (GPR41) and 43 (GPR43), in the spleen and colon of the allergic mice. Further analysis revealed that the GPR41 and GPR43 messenger RNA expression both positively correlated with the serum concentrations of transforming growth factor‐β and IFN‐γ (p < .05), but negatively with the serum concentrations of IL‐17, IL‐4, and IL‐6 in the L. acidophilus–treated group compared with the allergic group (p < .05). These results suggested that L. acidophilus protected against the development of allergic inflammation by improving the intestinal flora, as well as upregulating SCFAs and their receptors GPR41/43.     

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.     

Genome‐wide detection of CNVs associated with beak deformity in chickens using high‐density 600K SNP arrays

Beak deformity (crossed beaks) is found in several indigenous chicken breeds including Beijing‐You studied here. Birds with deformed beaks have reduced feed intake and poor production performance. Recently, copy number variation (CNV) has been examined in many species and is recognized as a source of genetic variation, especially for disease phenotypes. In this study, to unravel the genetic mechanisms underlying beak deformity, we performed genome‐wide CNV detection using Affymetrix chicken high‐density 600K data on 48 deformed‐beak and 48 normal birds using penncnv . As a result, two and eight CNV regions (CNVRs) covering 0.32 and 2.45 Mb respectively on autosomes were identified in deformed‐beak and normal birds respectively. Further RT‐qPCR studies validated nine of the 10 CNVRs. The ratios of six CNVRs were significantly different between deformed‐beak and normal birds (P < 0.01). Within these six regions, three and 21 known genes were identified in deformed‐beak and normal birds respectively. Bioinformatics analysis showed that these genes were enriched in six GO terms and one KEGG pathway. Five candidate genes in the CNVRs were further validated using RT‐qPCR. The expression of LRIG2 (leucine rich repeats and immunoglobulin like domains 2) was lower in birds with deformed beaks (P < 0.01). Therefore, the LRIG2 gene could be considered a key factor in view of its known functions and its potential roles in beak deformity. Overall, our results will be helpful for future investigations of the genomic structural variations underlying beak deformity in chickens.     

Application of the phosphomannose-isomerase/mannose selection system in the Agrobacterium-mediated transformation of Lonicera hypoglauca Miq.

Journal of Plant Biochemistry and Biotechnology - The dried buds of Lonicera hypoglauca Miq. have antipyretic, antidotal and anti-inflammatory properties and as Flos lonicerae are widely used in...