Comprehensive insights into the metabolism characteristics of small RNA Qrr4 in Vibrio alginolyticus.

Vibrio alginolyticus is an important foodborne pathogen that can infect both humans and marine animals and cause massive economic losses in aquaculture. Small noncoding RNAs (sRNAs) are emerging posttranscriptional regulators that affect bacterial physiology and pathological processes. In the present work, a new cell density-dependent sRNA, Qrr4, was characterized in V. alginolyticus based on a previously reported RNA-seq analysis and bioinformatics approach. The effects of Qrr4 actions on the physiology, virulence, and metabolism of V. alginolyticus were comprehensively investigated based on molecular biology and metabolomics approaches. The results showed that qrr4 deletion markedly inhibited growth, motility and extracellular protease activities. Additionally, nontargeted metabolism and lipidomics analyses revealed that qrr4 deletion induced significant disturbance of multiple metabolic pathways. The key metabolic remodelling that occurred in response to qrr4 deletion was found to involve phospholipid, nucleotide, carbohydrate and amino acid metabolic pathways, providing novel clues about a potential mechanism via which mutation of qrr4 could interfere with cellular energy homeostasis, modulate membrane phospholipid composition and inhibit nucleic acid and protein syntheses to regulate the motility, growth and virulence characteristics of V. alginolyticus. Overall, this study provides a comprehensive understanding of the regulatory roles of the new cell density-dependent sRNA Qrr4 in V. alginolyticus. KEY POINTS: • A novel cell density-dependent sRNA, Qrr4, was cloned in V. alginolyticus. •Qrr4 regulated growth and virulence factors of V. alginolyticus. • Phospholipid, nucleotide and energy metabolisms were modulated obviously by Qrr4.

Characterization of a cell density-dependent sRNA, Qrr, and its roles in the regulation of the quorum sensing and metabolism in Vibrio alginolyticus.

Vibrio alginolyticus is an important fish pathogen causing pandemic diseases in marine animals. Small noncoding RNAs (sRNAs) are important posttranscriptional modulators of gene expression and involved in the pathogenesis of bacterial pathogens. Thus far, no cell density-dependent sRNA has been reported in V. alginolyticus. In this study, a cell density-dependent sRNA, Qrr, predicted based on the previous RNA-Seq analysis of V. alginolyticus cultured at low cell density (LCD) and high cell density (HCD), was characterized. The Qrr mutant showed significantly impaired growth and decreased swimming and swarming ability, and increased biofilm formation, extracellular polysaccharide content, serine protease production, and LD50 values during zebrafish infection in contrast to the wild-type strain. Qrr modulates the master regulators LuxR and AphA in quorum sensing (QS) pathways possibly at the posttranscriptional level by base pairing with the 5'-untranslated regions (5'-UTRs). Meanwhile, both LuxR and AphA could directly bind to the promoter of qrr to activate or repress its transcription, respectively. Moreover, our unbiased metabolic approaches revealed that Qrr modulates a large quantity of metabolic and lipidomic pathways, including amino acids, purine and pyrimidine derivatives, tricarboxylic acid cycle (TCA cycle) intermediates, and lipids. Collectively, this work contributes to a systematic understanding of regulatory roles of the cell density-dependent sRNA, Qrr, in V. alginolyticus.

Effects and mechanisms of mineral amendment on thallium mobility in highly contaminated soils.

Thallium (Tl) is an extremely toxic element, whose toxicity is even higher than mercury, arsenic, and cadmium. It is of great significance to hinder the migration and transfer of Tl from soils to the plants. A synthetic mineral amendment (SMA), mainly composed of different silicates, was evaluated for its effects on the transformation and retention of Tl in two typical highly Tl-contaminated soils from Southwest China. The results indicated that the addition of mineral amendment increased the soil of the pH by 0.46-2.13 units and distinctly reduced the content of active thallium in the soils. The extent of Tl reduction was related to the morphological characteristics of the original soil In particular, the application of the mineral amendment transformed 25.8-52.5% of the active Tl fractions in the soils to the residual fraction at 60 d. Adding mineral amendment to the soils can provide conditions to facilitate Tl to enter the silicate crystal lattice. The results of XPS evidenced that the proportion of Tl(I) in the soil was greatly reduced after adding the mineral amendment.

Advanced treatment of effluents from an industrial park wastewater treatment plant by ferrous ion activated persulfate oxidation process.

The advanced oxidation technology, ferrous ion (Fe(II)) activated persulfate (PS) producing sulfate radicals, was used for the advanced treatment of effluent from an integrated wastewater treatment plant in a papermaking industrial park. Separate and interactive effects of PS dosage, Fe(II)/PS ratio and initial pH on chemical oxygen demand (COD) removal were analyzed by the response surface methodology (RSM). The results showed that Fe(II)-PS system was effective in COD removal from the secondary effluent. PS dosage was the most dominant factor with positive influence on COD removal, followed by initial pH value. The optimum conditions with COD removal of 54.4% were obtained at PS/COD of 2.2, initial pH of 6.47 and Fe(II)/PS of 1.89. UV-visible spectrum analysis showed that after RSM optimization, Fe(II)-PS system effectively degraded large organic molecules into small ones, and decreased humification degree of the effluent. Three-dimensional fluorescence analysis demonstrated that aromatic protein and fulvic substances were fully decomposed by the Fe(II)-PS treatment.

Effect of Peony (Paeonia ostii) Seed Meal Supplement on Enzyme Activities and Flavor Compounds of Chinese Traditional Soybean Paste during Fermentation.

Peony seed meal (PSM) is the by-product obtained from peony seeds after oil extraction. In this study, PSM was incorporated into traditional koji-making, and its impacts on koji enzyme activities and flavor compounds in final products were investigated. In the process of koji fermentation, the optimal addition ratio of PSM to soybean was determined as 7:3. Under this ratio, the maximum enzyme activities of neutral protease, amylase, and glucoamylase were 1177.85, 686.58, and 1564.36 U/g, respectively, and the koji obtained was subjected to maturation. During post-fermentation, changes in the fermentation characteristics of the paste samples were monitored, and it was found that compared to the soybean paste without PSM, the enzyme activities maintained at a relatively good level. The PSM soybean paste contained a total of 80 flavor compounds and 11 key flavor compounds (OAV ≥ 1), including ethyl isovalerate, isovaleric acid, hexanal, phenylacetaldehyde, 3-Methyl-1-butanol 4-heptanone, 2-pentylfuran, methanethiol ester caproate, isoamyl acetate, 3-methyl-4-heptanone, and isovaleraldehyde. These findings could be used to improve the quality of traditional fermented paste, enrich its flavor, and simultaneously promote PSM as a valuable resource for fermented foods.

Spatial Differentiation of Digital Rural Development and Influencing Factors in the Yellow River Basin, China.

The new development mode represented by the digital economy has provided new ideas for sustainable rural development. To comprehensively understand the status of digital rural development and propose scientific measures of rural revitalization in the Yellow River Basin (YRB), this study used counties as the research unit and data from 2020 to analyze the spatial differentiation characteristics and influencing factors by employing the Theil index, spatial autocorrelation analysis, and a geodetector model. The results showed that the digital rural development index in the YRB is slightly higher than it is in China overall, but the sub-index for the digital economy is lagging. The levels of digital rural development in the different reaches were lower reaches > middle reaches > upper reaches. Additionally, municipal districts and county-level cities have higher statuses than t general counties. Moreover, the decomposition of the Theil index shows that the intra-group differences in the upper reaches and general counties are the most important cause of the total differences. Moreover, the levels of digital rural development demonstrate spatial differences, with high and low levels in the east and west, respectively. An obvious reliable spatial correlation exists, and the spatial agglomeration featured with a similar level is significant. Finally, the influencing factors of spatial heterogeneity of digital rural development in the YRB and different reaches were different, with government expenditure being the main leading factor in the YRB and its upper reaches, while educational attainment and industrial structure are the leading factors in the middle reaches and lower reaches, respectively. The explanatory power of the interactions between the factors far exceeds that of a single factor, as shown through double-factor and nonlinear enhancement. This study provides a scientific reference for facilitating more targeted policy measures to achieving the goal of digital China and rural revitalization.

Switchable Normalization for Learning-to-Normalize Deep Representation.

We address a learning-to-normalize problem by proposing Switchable Normalization (SN), which learns to select different normalizers for different normalization layers of a deep neural network. SN employs three distinct scopes to compute statistics (means and variances) including a channel, a layer, and a minibatch. SN switches between them by learning their importance weights in an end-to-end manner. It has several good properties. First, it adapts to various network architectures and tasks (see Fig. 1). Second, it is robust to a wide range of batch sizes, maintaining high performance even when small minibatch is presented (e.g., 2 images/GPU). Third, SN does not have sensitive hyper-parameter, unlike group normalization that searches the number of groups as a hyper-parameter. Without bells and whistles, SN outperforms its counterparts on various challenging benchmarks, such as ImageNet, COCO, CityScapes, ADE20K, MegaFace and Kinetics. Analyses of SN are also presented to answer the following three questions: (a) Is it useful to allow each normalization layer to select its own normalizer? (b) What impacts the choices of normalizers? (c) Do different tasks and datasets prefer different normalizers? We hope SN will help ease the usage and understand the normalization techniques in deep learning. The code of SN has been released at https://github.com/switchablenorms.

Vehicle emission and atmospheric pollution in China: problems, progress, and prospects.

China has been the largest vehicle market in the world since 2009. The stalemate between the rapid development of the vehicle industry and delayed vehicle emission control has become increasingly prominent. Vehicle emission has become a significant source of air pollution in China's cities. Understanding the current barriers in the vehicle industry is necessary for the development of effective and sustainable measures and policy to manage vehicle-induced air pollution. This review provides insight into the circumstances and causes of vehicle-induced air pollution and outlines recent progress in policy-makers' long-term strategies and regulations. The development of an integrated mechanism of social participation, technical revolution, and regulatory innovation in vehicles, fuel, and roads is suggested to break the stalemate between air pollution and the automobile boom in China; the implications of this review extend to other countries facing the similar atmospheric pollution problems.

[Advanced Treatment of Effluent from Industrial Park Wastewater Treatment Plant by Ferrous Ion Activated Sodium Persulfate].

Fe(II) activated sodium persulfate (PS) technology was used for advanced treatment of effluent from industrial park wastewater treatment plant. Separate and combined effects of PS/COD, Fe(II)/PS and pH on COD and TOC removal were analyzed by the response surface methodology. Variations of organic substances before and after Fe(II)-PS oxidation were characterized by UV-Vis spectrometry, gel chromatography and three-dimensional fluorescence. PS/COD and Fe(II)/PS had significant effect on COD removal, while all the three factors had significant effect on TOC removal. The combined effect of PS/COD and pH had significant effect on COD removal. COD and TOC removal efficiencies reached 50.7% and 60.6% under optimized conditions of PS/COD 3.47, Fe(II)/PS 3.32 and pH 6.5. Fe(II)-PS oxidation converted macromolecular organic substances to small ones, and reduced contents of protein-, humic- and fulvic-like substances.