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.     

Development and Validation of a UPLC-MS/MS Method to Monitor Cephapirin Excretion in Dairy Cows following Intramammary Infusion

Cephapirin, a cephalosporin antibiotic, is used by the majority of dairy farms in the US. Fecal and urinary excretion of cephapirin could introduce this compound into the environment when manure is land applied as fertilizer, and may cause development of bacterial resistance to antibiotics critical for human health. The environmental loading of cephapirin by the livestock industry remains un-assessed, largely due to a lack of appropriate analytical methods. Therefore, this study aimed to develop and validate a cephapirin quantification method to capture the temporal pattern of cephapirin excretion in dairy cows following intramammary infusion. The method includes an extraction with phosphate buffer and methanol, solid-phase extraction (SPE) clean-up, and quantification using ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The LOQ values of the developed method were 4.02 µg kg⁻¹ and 0.96 µg L⁻¹ for feces and urine, respectively. This robust method recovered >60% and >80% cephapirin from spiked blank fecal and urine samples, respectively, with acceptable intra- and inter-day variation (<10%). Using this method, we detected trace amounts (µg kg⁻¹) of cephapirin in dairy cow feces, and cephapirin in urine was detected at very high concentrations (133 to 480 µg L⁻¹). Cephapirin was primarily excreted via urine and its urinary excretion was influenced by day (P = 0.03). Peak excretion (2.69 mg) was on day 1 following intramammary infusion and decreased sharply thereafter (0.19, 0.19, 0.08, and 0.17 mg on day 2, 3, 4, and 5, respectively) reflecting a quadratic pattern of excretion (Quadratic: P = 0.03). The described method for quantification of cephapirin in bovine feces and urine is sensitive, accurate, and robust and allowed to monitor the pattern of cephapirin excretion in dairy cows. This data will help develop manure segregation and treatment methods to minimize the risk of antibiotic loading to the environment from dairy farms.     

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.     

Mechanism of endotoxin-induced reduction in the number of beta-adrenergic receptors in dog livers: role of phospholipase A

The role of phospholipase A on the endotoxin-induced reduction in the number of beta-adrenergic receptors in dog liver plasma membranes was investigated. The results show that digestion of control liver plasma membranes with exogenous phospholipase A2 (0.2 unit/200 micrograms protein) decreased the specific binding of (-)-[3H]dihydroalprenolol by 37.3% (P less than 0.01) and reduced the number of receptor sites by 31.7% (P less than 0.05). These decreases in the specific binding and the number of beta-adrenergic receptors were completely reversible by the addition of phosphatidylcholine (0.2 mM). Endotoxin administration (2 hr postendotoxin) decreased the specific binding by 36% (P less than 0.05) and reduced the number of beta-adrenergic receptors by 33% (P less than 0.05), and these decreases were completely reversible by the addition of 0.2 mM phosphatidylcholine. Digestion of control liver membranes with exogenous phospholipase A2 decreased phosphatidylcholine and phosphatidylethanolamine levels by 50.6 and 51.2%, respectively, but increased lysophosphatidylcholine and lysophosphatidylethanolamine levels by 12- and 8.4-fold, respectively. Endotoxin administration decreased phosphatidylcholine and phosphatidylethanolamine contents by 21.4 and 23.8%, respectively, but increased lysophosphatidylcholine and lysophosphatidylethanolamine contents by 2.1- and 1.4-fold, respectively. In addition, endotoxin administration increased endogenous phospholipase A activity by 73.5%. Based on these results, it is suggested that the decreases in the specific binding and the number of beta-adrenergic receptors in dog livers during endotoxic shock are a result of phospholipase A activation.     

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.