Bioassessment of a Drinking Water Reservoir Using Plankton: High Throughput Sequencing vs. Traditional Morphological Method

Drinking water safety is increasingly perceived as one of the top global environmental issues. Plankton has been commonly used as a bioindicator for water quality in lakes and reservoirs. Recently, DNA sequencing technology has been applied to bioassessment. In this study, we compared the effectiveness of the 16S and 18S rRNA high throughput sequencing method (HTS) and the traditional optical microscopy method (TOM) in the bioassessment of drinking water quality. Five stations reflecting different habitats and hydrological conditions in Danjiangkou Reservoir, one of the largest drinking water reservoirs in Asia, were sampled May 2016. Non-metric multi-dimensional scaling (NMDS) analysis showed that plankton assemblages varied among the stations and the spatial patterns revealed by the two methods were consistent. The correlation between TOM and HTS in a symmetric Procrustes analysis was 0.61, revealing overall good concordance between the two methods. Procrustes analysis also showed that site-specific differences between the two methods varied among the stations. Station Heijizui (H), a site heavily influenced by two tributaries, had the largest difference while station Qushou (Q), a confluence site close to the outlet dam, had the smallest difference between the two methods. Our results show that DNA sequencing has the potential to provide consistent identification of taxa, and reliable bioassessment in a long-term biomonitoring and assessment program for drinking water reservoirs

Arabidopsis Transcriptome Analysis Reveals Key Roles of Melatonin in Plant Defense Systems

Melatonin is a ubiquitous molecule and exists across kingdoms including plant species. Studies on melatonin in plants have mainly focused on its physiological influence on growth and development, and on its biosynthesis. Much less attention has been drawn to its affect on genome-wide gene expression. To comprehensively investigate the role(s) of melatonin at the genomics level, we utilized mRNA-seq technology to analyze Arabidopsis plants subjected to a 16-hour 100 pM (low) and 1 mM (high) melatonin treatment. The expression profiles were analyzed to identify differentially expressed genes. 100 pM melatonin treatment significantly affected the expression of only 81 genes with 51 down-regulated and 30 up-regulated. However, 1 mM melatonin significantly altered 1308 genes with 566 up-regulated and 742 down-regulated. Not all genes altered by low melatonin were affected by high melatonin, indicating different roles of melatonin in regulation of plant growth and development under low and high concentrations. Furthermore, a large number of genes altered by melatonin were involved in plant stress defense. Transcript levels for many stress receptors, kinases, and stress-associated calcium signals were up-regulated. The majority of transcription factors identified were also involved in plant stress defense. Additionally, most identified genes in ABA, ET, SA and JA pathways were up-regulated, while genes pertaining to auxin responses and signaling, peroxidases, and those associated with cell wall synthesis and modifications were mostly down-regulated. Our results indicate critical roles of melatonin in plant defense against various environmental stresses, and provide a framework for functional analysis of genes in melatonin-mediated signaling pathways

Macrophage deletion of Noc4l triggers endosomal TLR4/TRIF signal and leads to insulin resistance

In obesity, macrophages drive a low-grade systemic inflammation (LSI) and insulin resistance (IR). The ribosome biosynthesis protein NOC4 (NOC4) mediates 40 S ribosomal subunits synthesis in yeast. Hereby, we reported an unexpected location and function of NOC4L, which was preferentially expressed in human and mouse macrophages. NOC4L was decreased in both obese human and mice. The macrophage-specific deletion of Noc4l in mice displayed IR and LSI. Conversely, Noc4l overexpression by lentivirus treatment and transgenic mouse model improved glucose metabolism in mice. Importantly, we found that Noc4l can interact with TLR4 to inhibit its endocytosis and block the TRIF pathway, thereafter ameliorated LSI and IR in mice.Macrophage inflammation promotes insulin resistance during diet-induced obesity. Here the authors show that macrophage NOC4L is decreased in humans and mice with obesity, that macrophage NOC4L deficiency aggravated high-fat diet induced inflammation and insulin resistance, and that NOC4L interacts with toll-like receptor 4, to inhibit endocytosis, and thus blocks TLF4/TRIF inflammatory signaling

Genetic characterization of androgenic progeny derived from Lolium perenne x Festuca pratensis cultivars

A successful androgenesis in amphidiploid Festulolium (Lolium perenne L. x Festuca pratensis Huds., 2n=4x=28) was obtained using PG-96 medium for embryo/callus induction. The green plant regeneration varied, and was 46 %, 35 % and 17 % for Bx350, Bx351 and Prior, respectively and over 800 green plants have been obtained. Androgenic progeny showed a large variation in freezing tolerance, 7 % of 292 progeny exceeding that of freezing hardy F. pratensis despite containing chromosomes of L. perenne, a more freezing-sensitive species. More than 60% of flowering 175 progeny produced dehiscent anthers with pollen stainability ranging from 5% to 85%. Androgenic plants contained 14 or 28 chromosomes. There were 188 (56 %), 204 (77 %) and 114 dihaploids (81 %) from Bx350, Bx351 and Prior, respectively. However, the nuclear DNA content varied significantly even between plants with the same chromosome number. Variation in DNA content reflected the genetic variation inherent in androgenic populations. High levels of chromosome pairing and recombination were observed due to close homology between genomes of L. perenne and F. pratensis.The definitive version is available at www.blackwell-synergy.co

A domain semantics-enhanced relation extraction model for identifying the railway safety risk

Abstract The identification of railway safety risk is important in ensuring continuous and stable railway operations. Most works fail to consider the important relation between detected objects. In addition, poor domain semantics directly degrades the final performance due to difficulty in understanding railway text. To solve these challenging issues, we introduce the triple knowledge from knowledge graph to model the railway safety risk with the knowledge interconnection mode. Afterward, we recast the identification of railway safety risk as the relation extraction task, and propose a novel and effective Domain Semantics-Enhanced Relation Extraction (DSERE) model. Specifically, we design a domain semantics-enhanced transformer mechanism that automatically enhances the railway semantics from a dedicated railway lexicon. We further introduce piece-wise convolution neural networks to explore the fine-grained features contained in the structure of triple knowledge. With the domain semantics and fine-grained features, our model can fully understand the domain text and thus improve the performance of relation classification. Finally, the DSERE model is used to identify the railway safety risk of south zone of China Railway, and achieves 81.84% AUC and 76.00% F1 scores on the real-world dataset showing the superiority of our proposed model

Deep Mutual Information Maximin for Cross-Modal Clustering

Cross-modal clustering (CMC) aims to enhance the clustering performance by exploring complementary information from multiple modalities. However, the performances of existing CMC algorithms are still unsatisfactory due to the conflict of heterogeneous modalities and the high-dimensional non-linear property of individual modality. In this paper, a novel deep mutual information maximin (DMIM) method for cross-modal clustering is proposed to maximally preserve the shared information of multiple modalities while eliminating the superfluous information of individual modalities in an end-to-end manner. Specifically, a multi-modal shared encoder is firstly built to align the latent feature distributions by sharing parameters across modalities. Then, DMIM formulates the complementarity of multi-modalities representations as an mutual information maximin objective function, in which the shared information of multiple modalities and the superfluous information of individual modalities are identified by mutual information maximization and minimization respectively. To solve the DMIM objective function, we propose a variational optimization method to ensure it converge to a local optimal solution. Moreover, an auxiliary overclustering mechanism is employed to optimize the clustering structure by introducing more detailed clustering classes. Extensive experimental results demonstrate the superiority of DMIM method over the state-of-the-art cross-modal clustering methods on IAPR-TC12, ESP-Game, MIRFlickr and NUS-Wide datasets

Phloem Loading Strategies and Water Relations in Trees and Herbaceous Plants1[W][OA]

Most herbaceous plants employ thermodynamically active mechanisms of phloem loading, whereas in many trees, the mechanism is passive, by diffusion. Considering the different water transport characteristics of herbs and trees, we hypothesized that water relations play a role in the adoption of phloem loading strategies. We measured whole-plant hydraulic conductance (Kp), osmolality, concentrations of polar metabolites, and key inorganic ions in recently mature leaves of 45 dicotyledonous species at midafternoon. Trees, and the few herbs that load passively, have low Kp, high osmolality, and high concentrations of transport sugars and total polar metabolites. In contrast, herbs that actively load sucrose alone have high Kp, low osmolality, and low concentrations of sugars and total polar metabolites. Solute levels are higher in sugar alcohol-transporting species, both herbs and trees, allowing them to operate at lower leaf water potentials. Polar metabolites are largely responsible for leaf osmolality above a baseline level (approximately 300 mm) contributed by ions. The results suggest that trees must offset low Kp with high concentrations of foliar transport sugars, providing the motivating force for sugar diffusion and rendering active phloem loading unnecessary. In contrast, the high Kp of most herbaceous plants allows them to lower sugar concentrations in leaves. This reduces inventory costs and significantly increases growth potential but necessitates active phloem loading. Viewed from this perspective, the elevation of hydraulic conductance marks a major milestone in the evolution of the herbaceous habit, not only by facilitating water transport but also by maximizing carbon use efficiency and growth

E-nose, E-tongue Combined with GC-IMS to Analyze the Influence of Key Additives during Processing on the Flavor of Infant Formula

In order to analyze the influence of key additives during processing on the flavor of infant formula, the headspace-gas chromatography-ion mobility spectrometry, electronic tongue, and electronic nose techniques were used to evaluate flavor during the processing of stage 1 infant formula milk powder (0–6 months), including the analysis of seven critical additives. A total of 41 volatile compounds were identified, involving 12 aldehydes, 11 ketones, 9 esters, 4 olefins, 2 alcohols, 2 furans, and 1 acid. The electronic nose metal oxide sensor W5S had the highest response, followed by W1S and W2S, illustrating that these three sensors had great effects on distinguishing samples. The response results of the electronic tongue showed that the three sensory attributes of bitter, salty, and umami, as well as the richness of aftertaste, were more prominent, which contributed significantly to evaluating the taste profile and distinguishing among samples. Raw milk is an essential control point in the flavor formation process of stage 1 infant formula milk powder. Demineralized whey powder is the primary source of potential off-flavor components in hydrolyzed milk protein infant formula. This study revealed the quality characteristics and flavor differences of key additives in the production process of stage 1 infant formula milk powder, which could provide theoretical guidance for the quality control and sensory improvement of the industrialized production of infant formula