Proteomic Analysis of Salivary Secretions from the Tea Green Leafhopper, Empoasca flavescens Fabrecius.

Saliva plays a crucial role in shaping the compatibility of piercing-sucking insects with their host plants. Understanding the complex composition of leafhopper saliva is important for developing effective and eco-friendly control strategies for the tea green leafhopper, Empoasca flavescens Fabrecius, a major piercing-sucking pest in Chinese tea plantations. This study explored the saliva proteins of tea green leafhopper adults using a custom collection device, consisting of two layers of Parafilm stretched over a sucrose diet. A total of 152 proteins were identified using liquid chromatography-tandem mass spectrometry (LC-MS/MS) following the filter-aided sample preparation (FASP). These proteins were categorized into six groups based on their functions, including enzymes, transport proteins, regulatory proteins, cell structure proteins, other proteins, and unknown proteins. Bioinformatics analyses predicted 16 secreted proteins, which were successfully cloned and transcriptionally analyzed across various tissues and developmental stages. Genes encoding putative salivary secretory proteins, including Efmucin1, EfOBP1, EfOBP2, EfOBP3, Efmucin2, low-density lipoprotein receptor-related protein (EfLRP), EFVg1, and EFVg2, exhibited high expressions in salivary gland (SG) tissues and feeding-associated expressions at different developmental stages. These findings shed light on the potential elicitors or effectors mediating the leafhopper feeding and defense responses in tea plants, providing insights into the coevolution of tea plants and leafhoppers. The study's conclusions open avenues for the development of innovative leafhopper control technologies that reduce the reliance on pesticides in the tea industry.

Total coliforms, microbial diversity and multiple characteristics of Salmonella in soil-irrigation water-fresh vegetable system in Shaanxi, China.

Global occurrences of foodborne disease outbreaks have been documented, involving fresh agricultural produce contaminated by various pathogens. This contamination can occur at any point in the supply chain. However, studies on the prevalence of total coliforms, Salmonella and microbial diversity in vegetable and associated environments are limited. This study aimed to assess 1) the number of total coliforms (n = 299) and diversity of microbial communities (n = 52); 2) the prevalence, antibiotic susceptibility, genomic characteristics, and potential transmission relationships of Salmonella in soil-irrigation water-vegetable system (n = 506). Overall, 84.28 % samples were positive to total coliforms, with most frequently detected in soil (100 %), followed by irrigation water (79.26 %) and vegetables (62.00 %). A seasonal trend in coliform prevalence was observed, with significantly higher levels in summer (P < 0.05). Detection rates of Salmonella in soil, vegetable and irrigation water were 2.21 %, 4.74 % and 9.40 %. Fourteen serotypes and sequence types (STs) were respectively annotated in 56 Salmonella isolates, ST13 S. Agona (30.36 %, 17/56), ST469 S. Rissen (25.00 %, 14/56), and ST36 S. Typhimurium (12.50 %, 7/56) were dominant serotypes and STs. Thirty-one (55.36 %) isolates were multi-drug resistant, and the resistance was most frequently found to ampicillin (55.36 %, 31/56), followed by to sulfamethoxazole (51.79 %, 29/56) and tetracycline (50.00 %, 28/56). The genomic characteristics and antibiotic resistance patterns of Salmonella isolates from soil, vegetables, and irrigation water within a coherent geographical locale exhibited remarkable similarities, indicating Salmonella may be transmitted among these environments or have a common source of contamination. Microbial alpha diversity indices in soil were significantly higher (P < 0.05) than that in vegetable and irrigation water. The microbial phylum in irrigation water covered that in the vegetable, demonstrating a significant overlap in the microbial communities between the vegetables and the irrigation water.

Antibiotic susceptibility and genomic analysis of ciprofloxacin-resistant and ESBLs-producing Escherichia coli in vegetables and their irrigation water and growing soil.

The rise of antibiotic resistance in Escherichia coli has become a major global public health concern. While there is extensive research on antibiotic-resistant E. coli from human and animal sources, studies on vegetables and their environments are limited. This study investigated the prevalence and characteristics of ciprofloxacin-resistant (CIPR) E. coli in 13 types of edible raw vegetables, along with their irrigation water and soil in Shaanxi, China. Of 349 samples collected (157 vegetables, 59 water, and 133 soil), a total of 48 positive samples were detected, with one CIPRE. coli strain isolated from each sample being selected for further analyses. A striking observation was its high prevalence in irrigation water at 44.1 %, markedly exceeding that in vegetables (12.0 %) and soil (4.5 %). The susceptibility of Forty-eight CIPRE. coli isolates was evaluated using the disc diffusion method for 18 different antibiotics, all these isolates were not only resistant to the tested fluoroquinolones antibiotics (levofloxacin, nalidixic acid), but also displayed a multi-drug resistance (MDR) pattern. Twenty-eight (58.3 %) of 48 CIPRE. coli isolates exhibited extended spectrum ß-lactamases (ESBLs) (CIPR-ESBLs) producing phenotype. Subsequently, whole-genome sequencing was performed on these 28 isolates. We identified 12 serotypes and STs each, with O101: H9 (35.7 %, 10/28) and ST10 (21.4 %, 6/28) being the most common. Further classification placed these isolates into five phylogenetic groups: A (57.1 %, 16/28), B1 (32.1 %, 9/28), D (3.6 %, 1/28), B2 (3.6 %,1/28), and F (3.6 %,1/28). Notelly, Identical ST types, serotypes and phylogroups were found in certain CIPR-ESBLs-producing E. coli from both vegetables and adjacent irrigation water. Genomic analysis of the 28 CIPR-ESBLs-producing E. coli isolates unveiled 73 resistance genes, associated with 13 amino acid mutations in resistance-determining regions (QRDRs) and resistance to 12 types of antibiotics. Each isolate was confirmed to carry both ESBLs and fluoroquinolone resistance genes, with the Ser83Ala mutation in GyrA (96.4 %, 27/28) being the most prevalent. A detailed analysis of Mobile Genetic Elements (MGEs) revealed that IncFIB and IncFII plasmid subtypes were most prevalent in 60.7 % and 67.9 % of isolates, respectively, with 75 % containing over 10 insertion sequences (IS) each. Furthermore, we observed that certain ESBL and PMQR genes were located on plasmids or in proximity to insertion sequences. In conclusion, our research highlights the widespread presence of CIPRE. coli in irrigation water and thoroughly examines the genetic characteristics of CIPR-ESBLs-producing E. coli strains, underlining the need for ongoing monitoring and management to reduce multidrug-resistant bacteria in vegetables and their environment.

CT synthesis from MR images using frequency attention conditional generative adversarial network.

Magnetic resonance (MR) image-guided radiotherapy is widely used in the treatment planning of malignant tumors, and MR-only radiotherapy, a representative of this technique, requires synthetic computed tomography (sCT) images for effective radiotherapy planning. Convolutional neural networks (CNN) have shown remarkable performance in generating sCT images. However, CNN-based models tend to synthesize more low-frequency components and the pixel-wise loss function usually used to optimize the model can result in blurred images. To address these problems, a frequency attention conditional generative adversarial network (FACGAN) is proposed in this paper. Specifically, a frequency cycle generative model (FCGM) is designed to enhance the inter-mapping between MR and CT and extract more rich tissue structure information. Additionally, a residual frequency channel attention (RFCA) module is proposed and incorporated into the generator to enhance its ability in perceiving the high-frequency image features. Finally, high-frequency loss (HFL) and cycle consistency high-frequency loss (CHFL) are added to the objective function to optimize the model training. The effectiveness of the proposed model is validated on pelvic and brain datasets and compared with state-of-the-art deep learning models. The results show that FACGAN produces higher-quality sCT images while retaining clearer and richer high-frequency texture information.

Boosting oxygen reduction via MnP nanoparticles encapsulated by N, P-doped carbon to Mn single atoms sites for Zn-air batteries.

An electrocatalyst of single-atomic Mn sites with MnP nanoparticles (NPs) on N, P co-doped carbon substrate was constructed to enhance the catalytic activity of oxygen reduction reaction (ORR) through one-pot in situ doping-phosphatization strategy. The optimized MnSA-MnP-980℃ catalyst exhibits an excellent ORR activity in KOH electrolyte with a half-wave potential (E1/2) of 0.88 V (vs. RHE), and the ORR current density of MnSA-MnP-980℃ maintained 97.9 % for over 25000 s chronoamperometric i-t measurement. When using as the cathode, the MnSA-MnP-980℃ displays a peak power density of 51 mW cm-2 in Zinc-Air batteries, which observably outperformed commercial Pt/C (20 wt%). The X-ray photoelectron spectroscopy reveal that the doped P atoms with a strong electron-donating effectively enhances electron cloud density of Mn SAs sites, facilitating the adsorption of O2 molecules. Meanwhile, the introduction of MnP NPs can regulate the electronic structure of Mn SAs sites, making Mn SAs active sites exist in a low oxidation state and are less positively charged, which can supply electrons for ORR process to narrow the adsorption energy barrier of ORR intermediates. This work constructs novel active sites with excellent ORR properties and provides valuable reference for the development of practical application.

Dual contrast attention-guided multi-frequency fusion for multi-contrast MRI super-resolution.

Objective. Multi-contrast magnetic resonance (MR) imaging super-resolution (SR) reconstruction is an effective solution for acquiring high-resolution MR images. It utilizes anatomical information from auxiliary contrast images to improve the quality of the target contrast images. However, existing studies have simply explored the relationships between auxiliary contrast and target contrast images but did not fully consider different anatomical information contained in multi-contrast images, resulting in texture details and artifacts unrelated to the target contrast images.Approach. To address these issues, we propose a dual contrast attention-guided multi-frequency fusion (DCAMF) network to reconstruct SR MR images from low-resolution MR images, which adaptively captures relevant anatomical information and processes the texture details and low-frequency information from multi-contrast images in parallel. Specifically, after the feature extraction, a feature selection module based on a dual contrast attention mechanism is proposed to focus on the texture details of the auxiliary contrast images and the low-frequency features of the target contrast images. Then, based on the characteristics of the selected features, a high- and low-frequency fusion decoder is constructed to fuse these features. In addition, a texture-enhancing module is embedded in the high-frequency fusion decoder, to highlight and refine the texture details of the auxiliary contrast and target contrast images. Finally, the high- and low-frequency fusion process is constrained by integrating a deeply-supervised mechanism into the DCAMF network.Main results. The experimental results show that the DCAMF outperforms other state-of-the-art methods. The peak signal-to-noise ratio and structural similarity of DCAMF are 39.02 dB and 0.9771 on the IXI dataset and 37.59 dB and 0.9770 on the BraTS2018 dataset, respectively. The image recovery is further validated in segmentation tasks.Significance. Our proposed SR model can enhance the quality of MR images. The results of the SR study provide a reliable basis for clinical diagnosis and subsequent image-guided treatment.

A new attempt to control volatile organic compounds (VOCs) pollution - Modification technology of biomass for adsorption of VOCs gas.

The detrimental impact of volatile organic compounds on the surroundings is widely acknowledged, and effective solutions must be sought to mitigate their pollution. Adsorption treatment is a cost-effective, energy-saving, and flexible solution that has gained popularity. Biomass is an inexpensive, naturally porous material with exceptional adsorbent properties. This article examines current research on volatile organic compounds adsorption using biomass, including the composition of these compounds and the physical (van der Waals) and chemical mechanisms (Chemical bonding) by which porous materials adsorb them. Specifically, the strategic modification of the surface chemical functional groups and pore structure is explored to facilitate optimal adsorption, including pyrolysis, activation, heteroatom doping and other methods. It is worth noting that biomass adsorbents are emerging as a highly promising strategy for green treatment of volatile organic compounds pollution in the future. Overall, the findings signify that biomass modification represents a viable and competent approach for eliminating volatile organic compounds from the environment.

A NEW DOSE DETERMINATION METHOD FOR HP(3) AND DP LENS FOR BETA REFERENCE RADIATION QUALITIES.

For the purpose of obtaining the smaller uncertainties for Hp(3) and Dp lens in 90Sr/90Y beta reference fields, a new dose determination method based on the Monte-Carlo simulation was proposed. The conversion coefficients from the absorbed dose in air, at the reference point of the extrapolation ionisation chamber, Dair, det to Hp(3; α) and the conversion factors from Dair, det to Dp lens(α) were calculated with EGSnrc, respectively, for the irradiation angles from 0° to 60°. Compared with the dose determination method in International Organization for Standardization (ISO) 6980 standard, the uncertainty reductions of 7.7-52.8% for Hp(3; α) and 7.9-55.0% for Dp lens(α) were achieved, respectively. In addition, for the conversion coefficients from the reference absorbed dose DR to Hp(3; α), the calculations were performed for more irradiation conditions, which are not included in the current ISO 6980 standard. For the calculations of the conversion factors from DR to Dp lens(α), the eye and head phantoms with Chinese characteristics were utilised, which makes the conversion factors more suitable for use in China.

The impacts of China's crops trade on virtual water flow and water use sustainability of the "Belt and Road".

Since the "Belt and Road" initiative was put forward, the trade of crops between China and the countries have increased markedly. Agriculture is the most water-consuming sector, the trade of crops could influence national water availability via virtual water embodied in the products. In order to gain an in-depth understanding of the water use of crops traded in countries along the "Belt and Road", from the perspective of import and export of China's crops, based on the characteristics and driving factors of virtual water trade, we proposed the Water Use Potential Index (WUPI) to assess sustainability of countries and their crops, and constructed a more comprehensive virtual water trade research framework. Results showed that the import and export of virtual water in 64 countries was dominated by green virtual water content from 2001 to 2017, and China was in a virtual water trade surplus. The Association of South-East Asian Nations was China's leading importer and exporter. The level of agricultural available water resources, the proportion of the agricultural population, the scale of agricultural production and the virtual water intensity could promote the growth of virtual water trade in crops between China and countries along the "Belt and Road", while economic model and the population structure played a restraining role. In terms of water use potential, China and Kazakhstan had great sustainable water use potential for crops, and the trade structure of other countries still needed to be further optimized. Understanding the virtual water trade in crops can provide a reference for the rational planning of crop cultivation and water resource conservation.

CALCULATION OF THE DOSE CONVERSION COEFFICIENTS FOR CHINESE EYE LENS UNDER PHOTON EXPOSURE.

In this work, the conversion coefficients from air kerma to the eye lens dose were calculated for photon exposures using the detailed eye and head Monte-Carlo (MC) model with the Chinese adult parameters. To verify the MC model and the simulation method, the conversion coefficients from fluence to the eye lens dose for mono-energy electrons (0.7-12 MeV) were calculated and compared with other studies. Then the conversion coefficients from air kerma to the doses in the entire lens and in the sensitive volume were calculated, respectively, for mono-energy photons (0.01-50 MeV) at different incidence angles (0-90°, in step of 15°). A small difference was found between the calculated conversion coefficient and the ICRP recommended value. The difference could be mainly due to the difference in their geometry characteristic of the eye and head models. In addition, the uncertainty analysis of the calculated conversion coefficients was performed in detail. The calculated dose conversion coefficient of the eye lens can be used to evaluate the eye lens dose for Chinese occupational staffs in external photon fields. And it can be used to determine the personal absorbed dose in the eye lens Dp lens in photon reference radiation fields.

TiO2 Coating Strategy for Robust Catalysis of the Metal-Organic Framework toward Energy-Efficient CO2 Capture.

High energy duty restricts the application of amine-based absorption in CO2 capture and limits the achievement of carbon neutrality. Although regenerating the amine solvent with solid acid catalysts can increase energy efficiency, inactivation of the catalyst must be addressed. Here, we report a robust metal-organic framework (MOF)-derived hybrid solid acid catalyst (SO42-/ZIF-67-C@TiO2) with improved acidity for promoting amine regeneration. The TiO2 coating effectively prevented the active components stripping from the surface of the catalyst, thus prolonging its lifespan. The well-protected Co-Nx sites and protonated groups introduced onto the TiO2 surface increased the amount and rate of CO2 desorption by more than 64.5 and 153%, respectively. Consequently, the energy consumption decreased by approximately 36%. The catalyzed N-C bond rupture and proton transfer mechanisms are proposed. This work provides an effective protection strategy for robust acid catalysts, thus advancing the CO2 capture with less energy duty.

One-Step Synthesized SO42-/ZrO2-HZSM-5 Solid Acid Catalyst for Carbamate Decomposition in CO2 Capture.

Amine-based CO2 capture technology requires high-energy consumption because the desorption temperature required for carbamate breakdown during absorbent regeneration is higher than 110 °C. In this study, we report a stable solid acid catalyst, namely, SO42-/ZrO2-HZSM-5 (SZ@H), which has improved Lewis acid sites (LASs) and Bronsted acid sites (BASs). The improved LASs and BASs enabled the CO2 desorption temperature to be decreased to less than 98 °C. The BASs and LASs of SZ@H preferred to donate or accept protons; thus, the amount and rate of CO2 desorption from spent monoethanolamine were more than 40 and 37% higher, respectively, when using SZ@H than when not using any catalyst. Consequently, the energy consumption was reduced by approximately 31%. A catalyzed proton-transfer mechanism is proposed for SZ@H-catalyzed CO2 regeneration through experimental characterization and theoretical calculations. The results reveal the role of proton transfer during CO2 desorption, which enables the feasibility of catalysts for CO2 capture in industrial applications.

Phosphorylation Mechanism of Phosphomevalonate Kinase: Implications for Rational Engineering of Isoprenoid Biosynthetic Pathway Enzymes.

The mevalonate pathway is of important clinical, pharmaceutical, and biotechnological relevance. However, lack of the understanding of the phosphorylation mechanism of the kinases in this pathway has limited rationally engineering the kinases in industry. Here the phosphorylation reaction mechanism of a representative kinase in the mevalonate pathway, phosphomevalonate kinase, was studied by using molecular dynamics and hybrid QM/MM methods. We find that a conserved residue (Ser106) is reorientated to anchor ATP via a stable H-bond interaction. In addition, Ser213 located on the α-helix at the catalytic site is repositioned to further approach the substrate, facilitating the proton transfer during the phosphorylation. Furthermore, we elucidate that Lys101 functions to neutralize the negative charge developed at the ß-, γ-bridging oxygen atom of ATP during phosphoryl transfer. We demonstrate that the dissociative catalytic reaction occurs via a direct phosphorylation pathway. This is the first study on the phosphorylation mechanism of a mevalonate pathway kinase. The elucidation of the catalytic mechanism not only sheds light on the common catalytic mechanism of the GHMP kinase superfamily but also provides the structural basis for engineering the mevalonate pathway kinases to further exploit their applications in the production of a wide range of fine chemicals such as biofuels or pharmaceuticals.