PbrWRKY62-PbrADC1 module involves in superficial scald development of Pyrus bretschneideri Rehd.fruit via regulating putrescine biosynthesis.

Putrescine plays a role in superficial scald development during the cold storage of pear fruit. However, the molecular mechanism behind this phenomenon has not been un-fully clarified until recently. In this study, a conjoint analysis of metabolites and gene expression profiles in the putrescine-metabolic pathway of P. bretschneideri Rehd. fruit followed by experimental validation revealed that PbrADC1, forming a homodimer in the chloroplast, was involved in putrescine biosynthesis and thus fruit chilling resistance. Additionally, the substrate-binding residue Cys546 in PbrADC1, whose activity was modified by H2O2, played a crucial role in arginine decarboxylation into agmatine. Through a combined analysis of the distribution of cis-acting elements in the PbrADC1 promoter as well as the expression profiles of related transcription factors (TFs), several TFs were identified as upstream regulators of PbrADC1 gene. Further investigation revealed that the nuclear PbrWRKY62 could directly bind to the W-box elements in the PbrADC1 promoter, activate its expression, enhance putrescine accumulation, and thus increase fruit chilling tolerance. In conclusion, our results suggest that the PbrWRKY62-PbrADC1 module is involved in the development of superficial scald in P. bretschneideri Rehd. fruit via regulating putrescine biosynthesis. Consequently, these findings could serve as valuable genetic resources for breeding scald-resistant pear fruit.

PbrbZIP15 promotes sugar accumulation in pear via activating the transcription of the glucose isomerase gene PbrXylA1.

The composition and abundance of soluble sugars in mature pear (Pyrus) fruit are important for its acceptance by consumers. However, our understanding of the genes responsible for soluble sugar accumulation remains limited. In this study, a S1-group member of bZIP gene family, PbrbZIP15, was characterized from pear genome through the combined analyses of metabolite and transcriptome data followed by experimental validation. PbrbZIP15, located in nucleus, was found to function in fructose, sucrose, and total soluble sugar accumulation in pear fruit and calli. After analyzing the expression profiles of sugar-metabolism-related genes and the distribution of cis-acting elements in their promoters, the glucose isomerase 1 gene (PbrXylA1), whose corresponding protein catalyzed the isomerization of glucose and fructose in vitro, was identified as a downstream target gene of PbrbZIP15. PbrbZIP15 could directly bind to the G-box element in PbrXylA1 promoter and activate its transcription, as evidenced by chromatin immunoprecipitation-quantitative PCR, yeast one-hybrid, electrophoretic mobility shift assay, and dual-luciferase assay. PbrXylA1, featuring a leucine-rich signal peptide in its N-terminal, was localized to the endoplasmic reticulum. It was validated to play a significant role in fructose, sucrose, and total soluble sugar accumulation in pear fruit and calli, which was associated with the upregulated fructose/glucose ratio. Further studies revealed a positive correlation between the sucrose content and the expression levels of several sucrose-biosynthesis-related genes (PbrFRK3/8, PbrSPS1/3/4/8, and PbrSPP1) in PbrbZIP15-/PbrXylA1-transgenic fruit/calli. In conclusion, our results suggest that PbrbZIP15-induced soluble sugar accumulation during pear development is at least partly attributed to the activation of PbrXylA1 transcription.

Risk-based regionalization approach for area-wide management of HLB vectors in the Mediterranean Basin.

Huanglongbing (HLB) is one of the most devastating citrus diseases worldwide. It is associated with the non-culture bacteria Candidatus Liberibacter spp., which can be transmitted by grafting and/or the psyllid vectors Diaphorina citri (ACP) and Trioza erytreae (AfCP). Although HLB has not been reported in the Mediterranean Basin to date, both vectors are present, and thus represent a serious threat to the citrus industry in this region. Resistant citrus cultivars or effective therapeutic treatments are not currently available for HLB. Nevertheless, area-wide pest management via coordinated management efforts over large areas has been implemented in Brazil, China and the USA for HLB control. This study proposes an open access flexible methodology to address area-wide management of both HLB vectors in the Mediterranean Basin. Based on a risk-based approach which considers climatic information and other variables that may influence vector introduction and spread, such as conventional, organic, abandoned and residential citrus areas as well as transportation corridors, an area-wide management division in pest management areas (PMAs) is proposed. The size and location of these PMAs were estimated by means of a hierarchical clustering algorithm with spatial constraints whose performance was assessed under different configuration scenarios. This proposal may assist policymakers and the citrus industry of the citrus-growing areas of the Mediterranean Basin in risk management planning in the case of the spread of HLB vectors or a possible introduction of the disease. Additionally, it may be a valuable resource to inform opinion dynamic models, enabling the identification of pivotal factors for the success of control measures.

Feature Distillation in Deep Attention Network Against Adversarial Examples.

Deep neural networks (DNNs) are easily fooled by adversarial examples. Most existing defense strategies defend against adversarial examples based on full information of whole images. In reality, one possible reason as to why humans are not sensitive to adversarial perturbations is that the human visual mechanism often concentrates on most important regions of images. A deep attention mechanism has been applied in many computer fields and has achieved great success. Attention modules are composed of an attention branch and a trunk branch. The encoder/decoder architecture in the attention branch has potential of compressing adversarial perturbations. In this article, we theoretically prove that attention modules can compress adversarial perturbations by destroying potential linear characteristics of DNNs. Considering the distribution characteristics of adversarial perturbations in different frequency bands, we design and compare three types of attention modules based on frequency decomposition and reorganization to defend against adversarial examples. Moreover, we find that our designed attention modules can obtain high classification accuracies on clean images by locating attention regions more accurately. Experimental results on the CIFAR and ImageNet dataset demonstrate that frequency reorganization in attention modules can not only achieve good robustness to adversarial perturbations, but also obtain comparable, even higher classification, accuracies on clean images. Moreover, our proposed attention modules can be integrated with existing defense strategies as components to further improve adversarial robustness.

ZnO@Bi5O7I Heterojunction Derived from ZIF-8@BiOI for Enhanced Photocatalytic Activity under Visible Light.

In the study, ZIF-8@BIOI composites were synthesized by the hydrothermal method and then calcined to acquire the ZnO@Bi5O7I composite as a novel composite for the photocatalytic deterioration of the antibiotic tetracycline (TC). The prepared ZnO@Bi5O7I composites were physically and chemically characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), Brunauer-Emmet-Teller (BET) surface area, UV-Vis diffuse reflectance spectroscopy (DRS), emission fluorescence spectra, transient photocurrent response, electrochemical impedance spectra and Mott-Schottky. Among the composites formed an n-n heterojunction, which increased the separation efficiency of electrons and holes and the efficiency of charge transfer. After the photocatalytic degradation test of TC, it showed that ZnO@Bi5O7I (2:1) had the best photodegradation effect with an 86.2% removal rate, which provides a new approach to the treatment of antibiotics such as TC in wastewater.

MOF composites derived BiFeO3@Bi5O7I n-n heterojunction for enhanced photocatalytic performance.

BiFeO3is a photocatalyst with excellent performance. However, its applications are limited due to its wide bandgap. In this paper, MIL-101(Fe)@BiOI composite material is synthesized by hydrothermal method and then calcined at high temperature to obtain BiFeO3@Bi5O7I composite material with high degradation capacity. Among them, an n-n heterojunction is formed, which improves the efficiency of charge transfer, and the recombination of light-generated electrons and holes promotes improved photocatalytic efficiency and stability. The result of photocatalytic degradation of tetracycline under visible light irradiation showed, BiFeO3@Bi5O7I (1:2) has the best photodegradation effect, with a degradation rate of 86.4%, which proves its potential as a photocatalyst.

Identification of a Chromosomal Deletion Mutation and the Dynamics of Two Major Populations of 'Candidatus Liberibacter asiaticus' in Its Hosts.

'Candidatus Liberibacter asiaticus' (Las) is the prominent species of Liberibacter associated with huanglongbing, a devastating disease of citrus worldwide. In this study, we report the identification of an ∼8.3-kb DNA region of the Las genome containing eight putative open reading frames flanked by two inverted repeats, which was not present in the Las str. psy62 genome. Comparisons with other genome sequences established this region as a unique genetic element associated with genome plasticity/instability. Primers specific for both the presence (Las wild type) and absence (Las mutant) of this region were designed to study the population dynamics and host adaptation of the two strains. Las populations with and/or without the wild-type strain were detected and differentiated in >2,300 samples that included psyllids, periwinkle, and several species of citrus. In psyllids, although a mixed population of the wild type and mutant was observed in most samples (88%), the wild-type Las was detected alone at a rate of 11%. In contrast, none of the infected citrus plants were positive for the wild type alone, which harbored either the mutant strain alone (8%) or a mixed population of the mutant and wild type (92%). Furthermore, the dynamics of these two major Las populations varied with different citrus hosts, whereas an in-depth study on grapefruit that did not rapidly succumb to disease revealed that the population of mutant alone increased with time, indicating that the absence of this genetic element is associated with the fitness of Las in planta under the selection pressure of its host.

Direct Fidelity Estimation of Quantum States Using Machine Learning.

In almost all quantum applications, one of the key steps is to verify that the fidelity of the prepared quantum state meets expectations. In this Letter, we propose a new approach solving this problem using machine-learning techniques. Compared to other fidelity estimation methods, our method is applicable to arbitrary quantum states, the number of required measurement settings is small, and this number does not increase with the size of the system. For example, for a general five-qubit quantum state, only four measurement settings are required to predict its fidelity with ±1% precision in a nonadversarial scenario. This machine-learning-based approach for estimating quantum state fidelity has the potential to be widely used in the field of quantum information.

Preparation of Room Temperature Vulcanized Silicone Rubber Foam with Excellent Flame Retardancy.

To retard the spread of fire in many cases with sealing materials is significant. A series of silicone rubber foam materials were prepared with room temperature vulcanization and foaming reactions. The morphology, chemical structure, cell structure, and thermal stability were investigated and results proved that the synthesis of silicone rubber was successful in a wide range of feed ratios. The fire-retardant tests were carried out to study the fire-proof property of the composite materials, and the excellent performance showed a promising prospect for wide application in sealing materials.

Identification and characterization of invertase family genes reveal their roles in vacuolar sucrose metabolism during Pyrus bretschneideri Rehd. fruit development.

23 invertase (PbrInvs) genes, including eight vacuolar invertases (PbrvacInvs), five cell wall invertases (PbrcwInvs) and 10 alkaline/neutral invertases (PbrA/N-Invs), were identified from P. bretschneideri Rehd. genome, with diverse chromosome locations, cis-acting elements, gene structures and motifs. Their expression profiles were tissue-specific, and postharvest light or temperature treatment would alter their expression profiles. During 'Dangshansuli' pear development, in association with visual/inner quality change was the alternations of invertase activity and the expression profiles of PbrInvs. In combination with results of subcellular sugar distribution as well as correlation analysis among sugar content, invertase activity and PbrInv mRNA abundance, PbrvacInv1 might be involved in sucrose decomposition during pear development. PbrvacInv1-GFP fusion protein mainly accumulated on the tonoplast (vacuolar membrane); meanwhile, transient overexpression of PbrvacInv1 in pear fruit would upregulate vacInv activity, causing higher fructose and lower sucrose when compared with that of the control. Furthermore, invertase inhibitor 5 (PbrInvInh5) could interact with PbrvacInv1.

Multi-View Gait Image Generation for Cross-View Gait Recognition.

Gait recognition aims to recognize persons' identities by walking styles. Gait recognition has unique advantages due to its characteristics of non-contact and long-distance compared with face and fingerprint recognition. Cross-view gait recognition is a challenge task because view variance may produce large impact on gait silhouettes. The development of deep learning has promoted cross-view gait recognition performances to a higher level. However, performances of existing deep learning-based cross-view gait recognition methods are limited by lack of gait samples under different views. In this paper, we take a Multi-view Gait Generative Adversarial Network (MvGGAN) to generate fake gait samples to extend existing gait datasets, which provides adequate gait samples for deep learning-based cross-view gait recognition methods. The proposed MvGGAN method trains a single generator for all view pairs involved in single or multiple datasets. Moreover, we perform domain alignment based on projected maximum mean discrepancy to reduce the influence of distribution divergence caused by sample generation. The experimental results on CASIA-B and OUMVLP dataset demonstrate that fake gait samples generated by the proposed MvGGAN method can improve performances of existing state-of-the-art cross-view gait recognition methods obviously on both single-dataset and cross-dataset evaluation settings.

Canine Olfactory Detection of a Non-Systemic Phytobacterial Citrus Pathogen of International Quarantine Significance.

For millennia humans have benefitted from application of the acute canine sense of smell to hunt, track and find targets of importance. In this report, canines were evaluated for their ability to detect the severe exotic phytobacterial arboreal pathogen Xanthomonas citri pv. citri (Xcc), which is the causal agent of Asiatic citrus canker (Acc). Since Xcc causes only local lesions, infections are non-systemic, limiting the use of serological and molecular diagnostic tools for field-level detection. This necessitates reliance on human visual surveys for Acc symptoms, which is highly inefficient at low disease incidence, and thus for early detection. In simulated orchards the overall combined performance metrics for a pair of canines were 0.9856, 0.9974, 0.9257 and 0.9970, for sensitivity, specificity, precision, and accuracy, respectively, with 1-2 s/tree detection time. Detection of trace Xcc infections on commercial packinghouse fruit resulted in 0.7313, 0.9947, 0.8750, and 0.9821 for the same performance metrics across a range of cartons with 0-10% Xcc-infected fruit despite the noisy, hot and potentially distracting environment. In orchards, the sensitivity of canines increased with lesion incidence, whereas the specificity and overall accuracy was >0.99 across all incidence levels; i.e., false positive rates were uniformly low. Canines also alerted to a range of 1-12-week-old infections with equal accuracy. When trained to either Xcc-infected trees or Xcc axenic cultures, canines inherently detected the homologous and heterologous targets, suggesting they can detect Xcc directly rather than only volatiles produced by the host following infection. Canines were able to detect the Xcc scent signature at very low concentrations (10,000× less than 1 bacterial cell per sample), which implies that the scent signature is composed of bacterial cell volatile organic compound constituents or exudates that occur at concentrations many fold that of the bacterial cells. The results imply that canines can be trained as viable early detectors of Xcc and deployed across citrus orchards, packinghouses, and nurseries.

Inoculation Period and Citrus Host Effect Establishment of New Infections of 'Candidatus Liberibacter asiaticus' Transmitted via Vegetative Grafting.

Vegetative grafting is a common method of transmitting and propagating 'Candidatus Liberibacter asiaticus', the bacterial species accepted as the causal agent of the citrus disease huanglongbing (HLB). Generally, infected tissue that is grafted to a receptor tree remains in place indefinitely to ensure transmission. In this study, individual HLB-symptomatic leaves were grafted as 'Ca. L. asiaticus' inoculum sources to receptor trees of six citrus types and removed after an inoculation period (IP) of 21, 51, or 81 days. The goal was to assess the effect of varying IPs on transmission of bacteria to the receptor tree and on the successful establishment of a new infection. Survival analysis of data from three trials showed a significantly reduced proportion of infected trees with an IP of 21 days compared with IPs of 51 and 81 days but that there was no significant difference in the proportion of infected trees between IPs of 51 and 81 days. In addition, the time to first detection of pathogen DNA in an infected tree was delayed significantly for the 21-day IP when compared with the 51- and 81-day IPs. Survival analysis showed that the probability of infection of sweet orange trees was significantly higher than for trees of five other citrus types throughout the experiment. There was no significant difference between the infection probabilities of these latter five citrus types. The data from this study show that successful infection by grafting is dependent upon the time of exposure to the inoculum, that shorter IPs increase the time needed to establish a systemic infection, and that citrus types vary in their overall susceptibility to infection by 'Ca. L. asiaticus'.

Canine olfactory detection of a vectored phytobacterial pathogen, Liberibacter asiaticus, and integration with disease control.

Early detection and rapid response are crucial to avoid severe epidemics of exotic pathogens. However, most detection methods (molecular, serological, chemical) are logistically limited for large-scale survey of outbreaks due to intrinsic sampling issues and laboratory throughput. Evaluation of 10 canines trained for detection of a severe exotic phytobacterial arboreal pathogen, Candidatus Liberibacter asiaticus (CLas), demonstrated 0.9905 accuracy, 0.8579 sensitivity, and 0.9961 specificity. In a longitudinal study, cryptic CLas infections that remained subclinical visually were detected within 2 wk postinfection compared with 1 to 32 mo for qPCR. When allowed to interrogate a diverse range of in vivo pathogens infecting an international citrus pathogen collection, canines only reacted to Liberibacter pathogens of citrus and not to other bacterial, viral, or spiroplasma pathogens. Canines trained to detect CLas-infected citrus also alerted on CLas-infected tobacco and periwinkle, CLas-bearing psyllid insect vectors, and CLas cocultured with other bacteria but at CLas titers below the level of molecular detection. All of these observations suggest that canines can detect CLas directly rather than only host volatiles produced by the infection. Detection in orchards and residential properties was real time, ∼2 s per tree. Spatiotemporal epidemic simulations demonstrated that control of pathogen prevalence was possible and economically sustainable when canine detection was followed by intervention (i.e., culling infected individuals), whereas current methods of molecular (qPCR) and visual detection failed to contribute to the suppression of an exponential trajectory of infection.

Sample Balancing for Deep Learning-Based Visual Recognition.

Sample balancing includes sample selection and sample reweighting. Sample selection aims to remove some bad samples that may lead to bad local optima. Sample reweighting aims to assign optimal weights to samples to improve performance. In this article, we integrate a sample selection method based on self-paced learning into deep learning frameworks and study the influence of different sample selection strategies on training deep networks. In addition, most of the existing sample reweighting methods mainly take per-class sample number as a metric, which does not fully consider sample qualities. To improve the performance, we propose a novel metric based on the multiview semantic encoders to reweight the samples more appropriately. Then, we propose an optimization mechanism to embed sample weights into loss functions of deep networks, which can be trained in end-to-end manners. We conduct experiments on the CIFAR data set and the ImageNet data set. The experimental results demonstrate that our proposed sample balancing method can improve the performances of deep learning methods in several visual recognition tasks.

Genome-wide analysis of polygalacturonase gene family from pear genome and identification of the member involved in pear softening.

BACKGROUND: Polygalacturonase (PG), as an important hydrolase participating in the degradation of pectin, plays an important role in softening process of fruit. However, information on PG gene family in pear genome and the specific member involved in fruit softening is still rudimentary. RESULTS: In this study, a total of 61 PG genes, which could be divided into six subclasses, were identified from the pear genome with diverse chromosome locations, gene structures, motifs and cis-acting elements. Most PbrPGs were derived from WGD/segmental duplication blocks, and purifying selection was the main driving force for their expansion. The expression profiles of PbrPGs in pear were tissue/development-stage/cultivar-dependent. During 'Housui' pear storage, associated with the reduction of firmness was the accumulation of PG activity. Totally, 28 PbrPGs were expressed during fruit storage, which could be classified into five categories based on different expression patterns; most demonstrated an increased trend. Of these, PbrPG6 were proposed to account for pear softening in combination of the phylogenetic and correlation analysis among firmness, PG activity and PbrPGs. By constructing the silencing vector, a higher firmness was observed in PbrPG6-silenced fruit when compared with that of the control (empty vector). In a further study, we found that the expression of PbrPG6 was regulated by postharvest 1-MCP/ethrel treatment, and several PbrERFs might function in this process. CONCLUSIONS: We identified 61 PbrPG genes from pear genome; of these, PbrPG6 was involved in fruit softening process; furthermore, the expression of PbrPG6 might be under the control of PbrERF. This study provides a foundation for future work aimed at elucidating the molecular mechanism underlying pear softening.

A probabilistic census-travel model to predict introduction sites of exotic plant, animal and human pathogens.

International travel offers an extensive network for new and recurring human-mediated introductions of exotic infectious pathogens and biota, freeing geographical constraints. We present a predictive census-travel model that integrates international travel with endpoint census data and epidemiological characteristics to predict points of introduction. Population demographics, inbound and outbound travel patterns, and quantification of source strength by country are combined to estimate and rank risk of introduction at user-scalable land parcel areas (e.g. state, county, zip code, census tract, gridded landscapes (1 mi2, 5 km2, etc.)). This risk ranking by parcel can be used to develop pathogen surveillance programmes, and has been incorporated in multiple US state/federal surveillance protocols. The census-travel model is versatile and independent of pathosystems, and applies a risk algorithm to generate risk maps for plant, human and animal contagions at different spatial scales. An interactive, user-friendly interface is available online (https://epi-models.shinyapps.io/Census_Travel/) to provide ease-of-use for regulatory agencies for early detection of high-risk exotics. The interface allows users to parametrize and run the model without knowledge of background code and underpinning data. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.

Using models to provide rapid programme support for California's efforts to suppress Huanglongbing disease of citrus.

We describe a series of operational questions posed during the state-wide response in California to the arrival of the invasive citrus disease Huanglongbing. The response is coordinated by an elected committee from the citrus industry and operates in collaboration with the California Department of Food and Agriculture, which gives it regulatory authority to enforce the removal of infected trees. The paper reviews how surveillance for disease and resource allocation between detection and delimitation have been addressed, based on epidemiological principles. In addition, we describe how epidemiological analyses have been used to support rule-making to enact costly but beneficial regulations and we highlight two recurring themes in the programme support work: (i) data are often insufficient for quantitative analyses of questions and (ii) modellers and decision-makers alike may be forced to accept the need to make decisions on the basis of simple or incomplete analyses that are subject to considerable uncertainty. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.

Effect of phosphate on amorphous iron mineral generation and arsenic behavior in paddy soils.

Arsenic (As) contamination was detected in paddy soils of Guangdong, China due to mining and weathering processes. Furthermore, As may be released into the soil and irrigation water during the application of phosphate (P). In this study, As behavior was assessed in three paddy soils (S6, S8 and TR) along the Hengshi river using batch and circular flow experiments with different phosphate application doses (0, 1, 5, 10, 50, 100 mg/L). The results indicate that pH variation (3-7) and higher phosphate concentrations in solution, can induce the release of As, with total As release ranked in the order: S6 > S8 > TR. In addition, AsV was the main state affected by phosphate in the circular soil solution. In particular, after 7 days of P10 application, the highest As concentration in S6, S8 and TR soil solutions reached 2298.4, 829.9 and 153.9 µg/L respectively, with the AsV state accounting for 93%, 97% and 18% of As. Some minerals were found to be generated in the middle container, most of which were amorphous iron or aluminum oxides and hydroxides, as confirmed by XRD. With mineral generation, the As concentration in soil solutions decreased to 314.2, 98.1 and 34.1 µg/L. The SEM results indicate that the minerals became more fine (<100 nm) when more P was applied. In addition, XPS, SEM-eds and elemental analysis results also revealed that As distribution was closely associated with iron minerals. Along with soil depth, P influenced the state and distribution of iron minerals and As in the topsoil, while phosphate increased the available As and reduced the amorphous iron mineral content in the soil. Therefore, it is essential to evaluate As behavior in paddy soils, to monitor and avoid potential food security risks.

Characterization of the Genes Involved in Malic Acid Metabolism from Pear Fruit and Their Expression Profile after Postharvest 1-MCP/Ethrel Treatment.

In this study, five genes involved in malic acid (MA) metabolism, including a cytosolic NAD-dependent malate dehydrogenase gene ( cyNAD-MDH), a cytosolic NADP-dependent malic enzyme gene ( cyNADP-ME), two vacuolar H+-ATPase genes ( vVAtp1 and vVAtp2), and one vacuolar inorganic pyrophosphatase gene ( vVPp), were characterized from pear fruit based on bioinformatic and experimental analysis. Their expression profile in "Housui" pear was tissue-specific, and their expression patterns during fruit development were diverse. During "Housui" pear storage, MA content decreased, which was associated with the downregulated transcripts of MA metabolism-related genes and cyNAD-MDH activity and higher cyNADP-ME activity. The response of MA metabolism to postharvest 1.5 µL L-1 1-MCP fumigation and 0.5 mL L-1 ethrel dipping was distinct: 1-MCP fumigation upregulated gene expression and cyNAD-MDH activity and suppressed cyNADP-ME activity, and thus maintained higher MA abundance when compared with those in the control; on the other hand, an opposite behavior was observed in ethrel-treated fruit.