Response of microbial communities in the phyllosphere ecosystem of tobacco exposed to the broad-spectrum copper hydroxide

Copper hydroxide is a broad-spectrum copper fungicide, which is often used to control crop fungal and bacterial diseases. In addition to controlling targeted pathogens, copper hydroxide may also affect other non-targeted microorganisms in the phyllosphere ecosystem. At four time points (before spraying, and 5, 10 and 15 days after fungicide application), the response of diseased and healthy tobacco phyllosphere microorganisms to copper hydroxide stress was studied by using Illumina high-throughput sequencing technology, and Biolog tools. The results showed that the microbiome communities of the healthy group were more affected than the disease group, and the fungal community was more sensitive than the bacterial community. The most common genera in the disease group were Alternaria, Boeremia, Cladosporium, Pantoea, Ralstonia, Pseudomonas, and Sphingomonas; while in the healthy group, these were Alternaria, Cladosporium, Symmetrospora, Ralstonia, and Pantoea. After spraying, the alpha diversity of the fungal community decreased at 5 days for both healthy and diseased groups, and then showed an increasing trend, with a significant increase at 15 days for the healthy group. The alpha diversity of bacterial community in healthy and diseased groups increased at 15 days, and the healthy group had a significant difference. The relative abundance of Alternaria and Cladosporium decreased while that of Boeremia, Stagonosporopsis, Symmetrospora, Epicoccum and Phoma increased in the fungal communities of healthy and diseased leaves. The relative abundance of Pantoea decreased first and then increased, while that of Ralstonia, Pseudomonas and Sphingomonas increased first and then decreased in the bacterial communities of healthy and diseased leaves. While copper hydroxide reduced the relative abundance of pathogenic fungi Alternaria and Cladosporium, it also resulted in the decrease of beneficial bacteria such as Actinomycetes and Pantoea, and the increase of potential pathogens such as Boeremia and Stagonosporopsis. After treatment with copper hydroxide, the metabolic capacity of the diseased group improved, while that of the healthy group was significantly suppressed, with a gradual recovery of metabolic activity as the application time extended. The results revealed changes in microbial community composition and metabolic function of healthy and diseased tobacco under copper hydroxide stress, providing a theoretical basis for future studies on microecological protection of phyllosphere

Characterization of a multidrug-resistant porcine Klebsiella pneumoniae sequence type 11 strain coharboring blaKPC-2 and fosA3 on two novel hybrid plasmids

The occurrence of carbapenemase-producing Enterobacteriaceae (CPE) poses a considerable risk for public health. The gene for Klebsiella pneumoniae carbapenemase-2 (KPC-2) has been reported in many countries worldwide, and KPC-2-producing strains are mainly of human origin. In this study, we identified two novel hybrid plasmids that carry either blaKPC-2 or the fosfomycin resistance gene fosA3 in the multiresistant K. pneumoniae isolate K15 of swine origin in China. The blaKPC-2-bearing plasmid pK15-KPC was a fusion derivative of an IncF33:A−:B− incompatibility group (Inc) plasmid and chromosomal sequences of K. pneumoniae (CSKP). A 5-bp direct target sequence duplication (GACTA) was identified at the boundaries of the CSKP, suggesting that the integration might have been due to a transposition event. The blaKPC-2 gene on pK15-KPC was in a derivative of ΔTn6296-1. The multireplicon fosA3-carrying IncN-IncR plasmid pK15-FOS also showed a mosaic structure, possibly originating from a recombination between an epidemic fosA3-carrying pHN7A8-like plasmid and a pKPC-LK30-like IncR plasmid. Stability tests demonstrated that both novel hybrid plasmids were stably maintained in the original host without antibiotic selection but were lost from the transformants after approximately 200 generations. This is apparently the first description of a porcine sequence type 11 (ST11) K. pneumoniae isolate coproducing KPC-2 and FosA3 via pK15-KPC and pK15-FOS, respectively. The multidrug resistance (MDR) phenotype of this high-risk K. pneumoniae isolate may contribute to its spread and its persistence

Direct field-to-pattern monolithic design of holographic metasurface via residual encoder-decoder convolutional neural network

Complex-amplitude holographic metasurfaces (CAHMs) with the flexibility in modulating phase and amplitude profiles have been used to manipulate the propagation of wavefront with an unprecedented level, leading to higher image-reconstruction quality compared with their natural counterparts. However, prevailing design methods of CAHMs are based on Huygens-Fresnel theory, meta-atom optimization, numerical simulation and experimental verification, which results in a consumption of computing resources. Here, we applied residual encoder-decoder convolutional neural network to directly map the electric field distributions and input images for monolithic metasurface design. A pretrained network is firstly trained by the electric field distributions calculated by diffraction theory, which is subsequently migrated as transfer learning framework to map the simulated electric field distributions and input images. The training results show that the normalized mean pixel error is about 3% on dataset. As verification, the metasurface prototypes are fabricated, simulated and measured. The reconstructed electric field of reverse-engineered metasurface exhibits high similarity to the target electric field, which demonstrates the effectiveness of our design. Encouragingly, this work provides a monolithic field-to-pattern design method for CAHMs, which paves a new route for the direct reconstruction of metasurfaces

Identification of Major QTLs Associated With First Pod Height and Candidate Gene Mining in Soybean

First pod height (FPH) is a quantitative trait in soybean [Glycine max (L.) Merr.] that affects mechanized harvesting. A compatible combination of the FPH and the mechanized harvester is required to ensure that the soybean is efficiently harvested. In this study, 147 recombinant inbred lines, which were derived from a cross between ‘Dongnong594’ and ‘Charleston’ over 8 years, were used to identify the major quantitative trait loci (QTLs) associated with FPH. Using a composite interval mapping method with WinQTLCart (version 2.5), 11 major QTLs were identified. They were distributed on five soybean chromosomes, and 90 pairs of QTLs showed significant epistatic associates with FPH. Of these, 3 were main QTL × main QTL interactions, and 12 were main QTL × non-main QTL interactions. A KEGG gene annotation of the 11 major QTL intervals revealed 8 candidate genes related to plant growth, appearing in the pathways K14486 (auxin response factor 9), K14498 (serine/threonine-protein kinase), and K13946 (transmembrane amino acid transporter family protein), and 7 candidate genes had high expression levels in the soybean stems. These results will aid in building a foundation for the fine mapping of the QTLs related to FPH and marker-assisted selection for breeding in soybean

Recombinant Human Endostatin Endostar Inhibits Tumor Growth and Metastasis in a Mouse Xenograft Model of Colon Cancer

To investigate the effects of recombinant human endostatin Endostar on metastasis and angiogenesis and lymphangiogenesis of colorectal cancer cells in a mouse xenograft model. Colon cancer cells SW620 were injected subcutaneously into the left hind flank of nude mice to establish mouse xenograft models. The mice were treated with normal saline or Endostar subcutaneously every other day. The growth and lymph node metastasis of tumor cells, angiogenesis and lymphangiogenesis in tumor tissue were detected. Apoptosis and cell cycle distribution were studied by flow cytometry. The expression of VEGF-A, -C, or -D in SW620 cells was determined by immunoblotting assays. Endostar inhibited tumor growth and the rate of lymph node metastasis (P < 0.01). The density of blood vessels in or around the tumor area was 12.27 ± 1.21 and 22.25 ± 2.69 per field in Endostar-treated mice and controls (P < 0.05), respectively. Endostar also decreased the density of lymphatic vessels in tumor tissues (7.84 ± 0.81 vs. 13.83 ± 1.08, P < 0.05). Endostar suppresses angiogenesis and lymphangiogenesis in the lymph nodes with metastases, simultaneously. The expression of VEGF-A, -C and -D in SW620 cells treated with Endostar was substantially lower than that of controls. Endostar inhibited growth and lymph node metastasis of colon cancer cells by inhibiting angiogenesis and lymphangiogenesis in a mouse xenograft model of colon cancer

A Study on the Impact of Fiscal Decentralization on Green Development from the Perspective of Government Environmental Preferences

Green development is necessary for China to carry out high-quality economic development. As an important institutional arrangement in the vertical government structure, fiscal decentralization supports regional green development. Local government environmental preferences indicate local environmental protection awareness and affect the process of regional green development to a certain extent. Based on the review of relevant theories and literature, this study conducts an empirical analysis based on Chinese provincial panel data from 2007 to 2019 using a two-way fixed effects model and a panel threshold model. Both revenue decentralization and expenditure decentralization have a U-shaped nonlinear relationship with the green development efficiency calculated by the superefficiency SBM model, which includes undesirable output. Neither factor has a positive effect on green development efficiency at this stage, while local government environmental preferences are positively connected to green development efficiency. Furthermore, a moderating effect is observed in the relationship between fiscal decentralization and green development efficiency. Under the same level of revenue decentralization or expenditure decentralization, the stronger the environmental preferences of the local authority are, the higher the green development efficiency. This moderating effect is more significant in coastal areas than inland areas. Further research reveals a threshold for the moderating effect of local government environmental preferences on fiscal decentralization on green development. When the environmental preferences of local government are below the threshold, both revenue decentralization and expenditure decentralization significantly inhibit the improvement in green development efficiency. After the threshold is passed, the negative effects of both on green development efficiency are markedly curtailed. Then, the government performance appraisal system should be further optimized, fiscal decentralization reform should be strengthened, local financial investment in environmental protection should be expanded, and synergistic regional development should be promoted. China&rsquo;s green development should be promoted to an advanced stage

Feature Recognition of Regional Architecture Forms Based on Machine Learning: A Case Study of Architecture Heritage in Hubei Province, China

Architecture form has been one of the hot areas in the field of architectural design, which reflects regional architectural features to some extent. However, most of the existing methods for architecture form belong to the field of qualitative analysis. Accordingly, quantitative methods are urgently required to extract regional architectural style, identify architecture form, and to and further provide the quantitative evaluation. Based on machine learning technology, this paper proposes a novel method to quantify the feature, form, and evaluation of regional architectures. First, we construct a training dataset—the Chinese Ancient Architecture Image Dataset (CAAID), in which each image is labeled by some experts as having at least one of three typical features such as “High Pedestal”, “Deep Eave” and “Elegant Gable”. Second, the CAAID is used to train our neural network model to identify three kinds of architectural features. In order to reveal the traditional forms of regional architecture in Hubei, we built the Hubei Architectural Heritage Image Dataset (HAHID) as our object dataset, in which we collected architectural images from four different regions including southeast, northeast, southwest, and northwest Hubei. Our object dataset is then fed into our neural network model to predict the typical features for those four regions in Hubei. The obtained quantitative results show that the feature identification of the architectural form is consistent with that of regional architectures in Hubei. Moreover, we can observe from the quantitative results that four geographic regions in Hubei show variation; for instance, the feature of the ‘elegant gable’ in southeastern Hubei is more evident, while the “Deep Eave” in the northwest is more evident. In addition, some new building images are selected to feed into our neural network model and the output quantitative results can effectively identify the corresponding feature style of regional architectures in Hubei. Therefore, our proposed method based on machine learning can be used not only as a quantitative tool to extract features of regional architectures, but also as an effective approach to evaluate architecture forms in the urban renewal process