Non‐pollinating cheater wasps benefit from seasonally poor performance of the mutualistic pollinating wasps at the northern limit of the range of Ficus microcarpa

1. Species interactions in tightly bound ecological mutualisms often feature highly specialised species' roles in which competitive exclusion may preclude multi‐species coexistence. Among the 800 fig (Ficus) species, it was originally considered that each was pollinated by their own wasp (Agaonidae). However, recent investigations show that this ‘one‐to‐one’ rule often breaks down, as fig species regularly host multiple agaonids but in ways suggesting that competitive processes still mediate biodiversity outcomes. 2. A phenological survey was conducted of the fig–fig wasp pair, Ficus microcarpa and its associated pollinating wasp, alongside its sister species, the cheating wasp, in Xishuangbanna, China. 3. Reproductive output underwent extreme seasonal variation. Seed and pollinator production fell markedly during cooler, drier months, although high levels of fig production continued. However, this resource was predominantly utilised by the cheater species, which offers no pollination services. Pollinators and cheaters rarely co‐occur, suggesting that temporal coexistence is constrained by competition for access to figs. 4. The overall findings indicate periodic rearrangements of mutualism dynamics, probably resulting from a strongly seasonal environment. Sympatric co‐occurrence may result from a window of opportunity for a functionally divergent agaonid, potentially due to constraints on the main pollinator in adapting to variable year‐round conditions that prevent competitive exclusion.     

Association between FABP2 Ala54Thr polymorphisms and type 2 diabetes mellitus risk: a HuGE Review and Meta‐Analysis

Many studies have examined the association between the FABP2 (rs1799883) Ala54Thr gene polymorphism and type 2 diabetes mellitus risk (T2DM) in various populations, but their results have been inconsistent. To assess this relationship more precisely, A HuGE review and meta‐analysis were performed. The PubMed and CNKI database was searched for case‐control studies published up to April 2014. Data were extracted and pooled odds ratios (OR) with 95% confidence intervals (CI) were calculated. Ultimately, 13 studies, comprising 2020 T2DM cases and 2910 controls were included. Overall, for the Thr carriers (Ala/Thr and Thr/Thr) versus the wild‐type homozygotes (Ala/Ala), the pooled OR was 1.18 (95% CI = 1.04–1.34, P = 0.062 for heterogeneity), for Thr/Thr versus Ala/Ala the pooled OR was 1.17 (95% CI = 1.05–1.41 P = 0.087 for heterogeneity). In the stratified analysis by ethnicity, the significantly risks were found among Asians but not Caucasians. This meta‐analysis suggests that the FABP2 (rs1799883) Ala54Thr polymorphisms are associated with increased susceptibility to T2DM risk among Asians but not Caucasians.     

Cloning and characterization of a SnRK1-encoding gene from <Emphasis Type="Italic">Malus hupehensis</Emphasis> Rehd. and heterologous expression in tomato

Sucrose non-fermenting-1-related protein kinase-1 (SnRK1) plays an important role in metabolic regulation in plant. To understand the molecular mechanism of amino acids and carbohydrate metabolism in Malus hupehensis Rehd. var. pinyiensis Jiang (Pingyi Tiancha, PYTC), a full-length cDNA clone encoding homologue of SnRK1 was isolated from PYTC by Rapid Amplification of cDNA Ends (RACE). The clone, designated as MhSnRK1, contains 2063 nucleotides with an open reading frame of 1548 nucleotides. The deduced 515 amino acids showed high identities with other plant SnRK1 genes. Quantitative real-time PCR analysis revealed this gene was expressed in roots, stems and leaves. Exposing seedlings to nitrate caused and initial decrease in expression of the MhSnRK1 gene in roots, leaves and stems in short term. Ectopic expression of MhSnRK1 in tomato mainly resulted in higher starch content in leaf and red-ripening fruit than wild-type plants. This result supports the hypothesis that overexpression of SnRK1 causes the accumulation of starch in plant cells. All the results suggest that MhSnRK1 may play important roles in carbohydrate and amino acid metabolisms.     

Solution structure of the N‐terminal domain of DC‐UbP/UBTD2 and its interaction with ubiquitin

DC‐UbP/UBTD2 is a ubiquitin (Ub) domain‐containing protein first identified from dendritic cells, and is implicated in ubiquitination pathway. The solution structure and backbone dynamics of the C‐terminal Ub‐like (UbL) domain were elucidated in our previous work. To further understand the biological function of DC‐UbP, we then solved the solution structure of the N‐terminal domain of DC‐UbP (DC‐UbP_N) and studied its Ub binding properties by NMR techniques. The results show that DC‐UbP_N holds a novel structural fold and acts as a Ub‐binding domain (UBD) but with low affinity. This implies that the DC‐UbP protein, composing of a combination of both UbL and UBD domains, might play an important role in regulating protein ubiquitination and delivery of ubiquitinated substrates in eukaryotic cells.     

Diet of the Indochinese silvered langur (Trachypithecus germaini) in Kien Luong Karst area,Kien Giang Province

The Indochinese silvered langur (Trachypithecus germaini) is distributed to the west of Mekong River in Cambodia, Lao PDR, Thailand and Vietnam. During a two‐year study, from May 2014 to May 2016, we collected 320.44 hr of behavior, with 17,040 feeding bouts recorded (142 hr) for T. germaini on Chua Hang Karst Mountain, Kien Luong District, Kien Giang Province, Vietnam. Feeding accounted for 45% of the Indochinese silvered langurs’ activity budget. The plant diet of the Indochinese silvered langurs was principally composed of young leaves (58%), followed by mature leaves (9.5%), fruits (22.7%), flowers (4.7%), buds (3.3%), petioles (1.2%), and other (0.5%). A total of 58 plant species were fed on by the silvered langurs, and leaves of eight species (Phyllathus reticulatus, Ficus rumphii, Ficus tinctoria, Ficus microcarpa, Cayratia trifolia, Streblus ilicifolia, Combretum latifolium, and Streblus asper) were fed on throughout the year. P. reticulatus was most frequently eaten (13.9% feeding time, n = 1,733). Food selection differed significantly between months and seasons. The Indochinese silvered langurs ate 27 plant species in the wet season compared with 23 plant species in the dry season. Leaf chemical composition of two food categories, 16 eaten species (with 10 most frequently consumed species and six least consumed species), and four noneaten species, were analyzed. Feeding samples from eaten species in the Indochinese silvered langurs's diet contained lower amounts of condensed tannin, lignin, protein, ash, and lipids, but a higher amount of total sugar compared with samples from noneaten species. Furthermore, the most frequently consumed species contained lower amounts of lignin compared with the less frequently consumed species. Using a generalized linear model with five variables, including neutral detergent fiber (NDF), total sugar, lignin, lipid, and calcium (Ca) indicated that NDF positively correlated and lignin content negatively correlated with feeding records in the diet of these langur.     

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.