Jiangxi Agricultural University

The widespread antimicrobial resistance (AMR) problem poses a serious health threat, leaving few drug choices, including tigecycline, to treat multidrug resistance pathogens. However, a plasmid-borne tigecycline resistance gene cluster, tmexCD1-toprJ1, emerged and conferred tigecycline resistance. In this study, we identified two novel subtypes, tmexCD2.3-toprJ2.3 and tmexCD2.4-toprJ1b, obtained from three chicken-origin Pseudomonas putida isolates. Two types of megaplasmids were found as the vital vehicle of these tmexCD-toprJ variants. Phylo- genetic and genomic analysis indicated the two variants were mainly distributed in Pseudomonas and acted as an evolved intermediated state precursor of tmexCD2-toprJ2. Further gene cloning assay revealed both the expres- sion of tmexCD2.3-toprJ2.3 and tmexCD2.4-toprJ1b could confer multiple antimicrobial resistance, mediating 8- to 16-fold increase of tigecycline MIC. Importantly, two key nucleotide differences in promoter region influence the promoter activity between PtmexC2.3 and PtmexC2.4, while the downregulation effect of TNfxB on the transcrip- tional expression level of tmexCD2.3-toprJ2.3 and tmexCD2.4-toprJ1b were observed. The emergency of two novel tmexCD-toprJ variants necessitates preventive measures to curb their spread and highlights concerns about more emerging tmexCD-toprJ variants.

With the rapid development of artificial intelligence technology, an increasing number of village-related modeling problems have been addressed. However, first, the exploration of village-related watershed fine-grained classification problems, particularly the multi-view watershed fine-grained classification problem, has been hindered by dataset collection limitations; Second, village-related modeling networks typically employ convolutional modules for attentional modeling to extract salient features, yet they lack global attentional feature modeling capabilities; Lastly, the extensive number of parameters and significant computational demands render village-related watershed fine-grained classification networks infeasible for end-device deployment. To tackle these challenges, we introduce a multi-view attention mechanism designed for precise watershed classification, leveraging knowledge distillation techniques, abbreviated as MANet-KD. Specifically, first, we have developed the inaugural multi-view watershed classification dataset, termed MVWD.Second, we introduce a cross-view attention module (CVAM), which models salient features from intersecting views with global attention, enhancing the accuracy and precision of watershed classification. This module enhances fine-grained classification accuracy. Based on the above proposed CVAM, we propose a heavyweight MANet-Teacher and a lightweight MANet-Student, and finally, we introduce an Attention Knowledge Distillation (AKD) strategy that effectively transfers critical feature knowledge from the teacher network to the student network, utilizing the AKD approach for enhanced learning outcomes. The experimental results show that the proposed MANet-Teacher achieves state-of-the-art performance with 78.51% accuracy, and the proposed MANet-Student achieves comparable performance to MANet-Teacher with 6.64M parameters and 1.68G computation. The proposed MANet-KD achieves a good balance of performance and efficiency in the multi-view fine-grained watershed classification task. To facilitate further research in multi-view fine-grained watershed classification, all datasets, codes, and benchmark outcomes will be made available to the public. https://github.com/Jack13026212687/MANet-KD.

A convenient method is proposed using a heat-treatable volatile template to prepare hierarchical porous biochar (HPB). Litsea cubeba leaves and ZIF-8 served as carbon source and volatile hard template, respectively. The good compatibility between ZIF-8 and biomass facilitated their uniform dispersion, and the thermal decomposition of ZIF-8 created abundant pores in the HPB. By using ZIF-8 with different sizes as “modulators”, the textural properties of HPB can be controlled. The HPB derived from 200 nm-sized ZIF-8 exhibited ultra-high specific surface area, rich macro-meso-micro porous structure, and excellent electrocatalytic activity, which makes HPB-200 an effective electrochemical sensing platform. The sensor demonstrated an ultralow detection limit (0.2 nM) of Ponceau 4R, showing significant application potential in the field of electroanalytical sensing. Graphical Abstract Schematic illustration of a convenient method using a heat-treatable volatile template to prepare hierarchical porous biochar (HPB)

Background Ginkgo biloba L., an iconic living fossil, challenges traditional views of evolutionary stasis. While nuclear genomic studies have revealed population structure across China, the evolutionary patterns reflected in maternally inherited plastomes remain unclear, particularly in the Sichuan Basin - a potential glacial refugium that may have played a crucial role in Ginkgo’s persistence. Results Analysis of 227 complete plastomes, including 81 newly sampled individuals from the Sichuan Basin, revealed three distinct maternal lineages differing from known nuclear genome patterns. We identified 170 sequence variants and extensive RNA editing (235 sites) with a bias toward hydrophobic amino acid conversions, suggesting active molecular evolution. A previously undocumented haplotype (IIA2), predominant in western Sichuan Basin populations, showed close genetic affinity with rare refugial haplotypes. Western populations exhibited higher haplotypic diversity and distinctive genetic structure, supporting the basin’s role as both glacial refugium and corridor for population expansion. Ancient trees (314–784 years) provided evidence for interaction between natural processes and historical human dispersal in shaping current genetic patterns. Conclusions Our findings demonstrate substantial genetic diversity within Sichuan Basin Ginkgo populations and reveal dynamic molecular evolution through plastome variation and RNA editing patterns, challenging the notion of evolutionary stasis in this living fossil. This study provides crucial genomic resources for understanding Ginkgo’s evolution and informs conservation strategies for this endangered species.

In the intelligent harvesting of eggplant, the lack of in situ identification technology makes it challenging to determine the maturity of purple eggplant fruit. The length of the fruit‐setting date can determine when the eggplant is ready to be harvested. This study uses deep learning techniques to predict the date of fruit maturity. First, we proposed a fruit‐setting days prediction method based on fruit spectroscopy and neural networks. Second, we collected the field in situ spectral data of purple eggplant fruit during 15–33 days of fruit setting using a portable spectrometer, covering 500–1000 nm. A fruit‐setting time regression network combining multi‐scale convolution, multi‐head attention mechanism, and long short‐term memory recurrent neural network was constructed using the collected in situ spectral data. The model demonstrated better fitting performance than traditional machine learning models such as backpropagation neural network, random forest, support vector machine, and partial least squares regression in the regression task of fruit‐setting days. After testing various spectral preprocessing methods, the best fitting effect was found on the standard normal variate–processed dataset, with R² of 0.876 and RMSE(root mean square error) of 2.148 days. Furthermore, the feasibility of each model module was analyzed in depth through ablation experiments, confirming each component's role in improving the model's performance. The network attention weight was also analyzed, and the model has strong detail mining ability in a specific spectral interval. In summary, the combination of visible and near‐infrared spectroscopy and attention cycle neural network is an effective method to predict the fruit‐setting days of purple eggplant fruit. Practical Application A prediction method of fruit‐setting days based on fruit spectral characteristics and recurrent neural network regression was proposed. A novel approach to detecting and disclosing in situ surface VIS‐NIRS reflectance data of eggplant fruit during ripening is presented for the first time. A set of long‐term and short‐term memory networks based on multi‐scale convolution and multi‐head attention mechanisms was constructed for spectral data fitting. Through the ablation test method and attention weight analysis, the function of each module in the network and the interpretability of feature extraction are explored.

Hibernation is a necessary means for animals to maintain survival while coping with low temperatures and food shortages. While most studies have largely focused on mammalian hibernation, its reptilian equivalent has been less studied. In order to provide insights into the energy metabolism and potential microbial regulatory mechanisms in hibernating snakes, the serum, liver, gut content samples were measured by multi-omic methods. Here we show the active snakes have more vigorous lipid metabolism, whereas snakes in hibernation groups have higher sphingolipid metabolism. Furthermore, the results indicate that the potential energy supply pathway was gluconeogenesis. Microbial analysis reveals that Proteobacteria and Firmicutes showed dynamic changes with the transformation among active, pre-hibernation and hibernation periods. The correlation analysis reveals the potential role of Romboutsia, Providencia and Vagococcus in regulating above metabolism by producing certain metabolites. The results advance the understanding of the complex energy-saving strategy in hibernating poikilotherms.

The utilization of manure resources is an important measure to promote the development of agricultural green low-carbon cycle and solve the challenges associated with the current large-scale development of the livestock and poultry breeding industry. Based on the survey data of pig farmers in Qingdao, Shandong Province, China, this paper constructs a theoretical analysis framework of pig breeding scale and technical cognition on the utilization behavior of livestock and poultry manure resources of pig farmers. The binary Logit model and the moderating effect model are used to deeply explore the scale effect of breeding scale on the utilization behavior of pig farmers’ manure resources, and the moderating effect of technical cognition on the influence of breeding scale on the utilization behavior of manure resources. First, at the present stage, pig farmers show certain differences in the resource utilization of manure. Due to the differences in the personal characteristics, family characteristics, and breeding characteristics of pig farmers, the influencing factors of resource utilization of pig farmers of different scales are different; Second, the scale of pig breeding has a significant positive promoting effect on the resource utilization of manure, increasing the probability of pig farmers to treat manure, guiding retail and small-scale farmers to moderately expand the scale of breeding, gradually moving to large-scale breeding, realizing centralized management and resource utilization of manure, and reducing the unit cost of manure treatment. Third, technical ease of use has a positive regulatory effect on pig breeding scale and manure resource utilization behavior. When pig farmers perceive that the technology of manure resource utilization is easy to use, they will increase the probability of participating in the resource utilization of manure, reduce the environmental pollution caused by improper disposal of manure, and promote the low-carbon and circular development of livestock and poultry industry. Based on the above findings, this paper aims to provide practical enlightenment for policy makers and researchers to strengthen the environmental governance and sustainable development of livestock industry.

Significant differences in life-history traits between the southern population (S) and northern (N) population of the cabbage beetle Colaphellus bowringi make it an excellent model for studying inheritance in this insect. In the present study, we observed the life-history traits of pure strains, F 1 , reciprocal backcross and reciprocal F 2 progeny under a photoperiod of L:D 15:9 h at 22 °C. The S population had shorter larval development time, longer pupal time, higher body weight, growth rate and weight loss compared with the N population. In the F 1 testing, the larval development time and body weight in hybrid populations were intermediate between the parents, and the paternal parents played a greater role in determining the larval development time, while the maternal parents exhibited a greater role in determining the body weight. The pupal time of hybrid populations was significantly shorter than that of the parents. In the reciprocal backcross testing, both father and grandfather affected the larval development time, while both mother and grandmother affected the body weight. Consistently, in the reciprocal F 2 cross testing, the grandfather was more influential in determining the larval development time, and grandmother was more important in determining the body weight. In all tested populations, females had greater body weight, higher growth rate and weight loss than males. Hybridization pattern did not affect sex dimorphism and sex ratio. Overall, these findings suggest that different pathways (maternal or paternal effects) were involved in the inheritance of various life-history traits in C. bowringi .

In contrast to other countries, China's agricultural production faces the challenges of aging and feminization, which have a tremendous impact on food security. The purpose of this research was to reveal the correlations between aging and feminization and agricultural production factor input and its heterogeneity. This was evaluated using the ordinary least squares (OLS) model. The research found that the aging of farming did not correlate with the input of land factor and employment input. However, the feminization of farming significantly correlated with the input of land factor and employment input. In particular, an increase in the feminization of farming by one standard deviation reduced the land factor input by 18.9% and employment input by 31.3%. Second, agricultural aging and feminization had a positive and significant effect on agricultural machinery input but a negative and significant effect on material input. The instrumental variable method test results were consistent with those of the main regression. Third, heterogeneity analysis showed that the correlations between aging and feminization and the input of land, employment, agricultural machinery, and materials were significantly different with different educational levels of house heads and the proportion of agricultural income. Therefore, this study provides a reference for adjusting the rural labor structure and accumulating advanced rural production factors.

Background Cotton is a non-edible fiber crop with considerable potential for the remediation of copper-polluted soil. However, the Cu toxicity tolerance mechanism in cotton remains largely obscure. To address the issue, we first identified two cotton lines contrasting in response to Cu toxicity by examining 12 morphological and physiological attributes of 43 origin scattered cotton genotypes under Cu excess. Then both lines were subjected to a comprehensive comparative study, aiming to unravel the cotton Cu tolerance mechanism through integrated morphological, physio-biochemical, Cu uptake and distribution, and related molecular expression analyses. Results Based on the phenotypic values and corresponding tolerance indexes of 12 parameters, A2304 and A1415 were identified as Cu-tolerant and -sensitive, respectively. Compared to A1415, A2304 exhibited significantly higher antioxidant enzyme activities and non-enzymatic antioxidant levels, producing fewer amounts of reactive oxygen species and a lower level of malonyldialdehyde. On Cu excess, A2304 accumulated lower concentrations of Cu ions in various plant parts and subcellular components, and fewer Cu ions were presented in active chemical forms. However, the total Cu uptake amount per plant did not differ between both lines due to larger plant biomass with A2304. In contrast to A1415, Cu stress activated or increased the expressions of Cu homeostasis regulator (GhSPL7) and genes responsible for Cu delivery (GhCCS, GhCOX17), chelation (GhMT2), and compartmentation into vacuoles (GhHMA5), while inactivating or decreasing the expressions of genes accounting for Cu uptake (GhCOPT1) and Cu exporting from vacuoles (GhCOPT5) in the root cell with A2304. Additionally, A2304 may impede the root cell wall from binding Cu ions by enhancing the pectin methylesterification degree by up-regulating GhPMEI3 and GhPMEI9 encoding pectin methylesterase inhibitor and stabilizing the cell wall organization by down-regulating GhPLY8 and GhPLY20 encoding pectate lyases. Conclusions To cope with Cu toxicity, the Cu-tolerant genotype activates its antioxidative defense system, immobilizing chemically active Cu ions, and lowering the Cu uptake, bioavailability and immigration within cells by regulating the expressions of genes related to Cu uptake, transport, delivery and cell wall metabolism. This comprehensive comparison study provides insights into breeding Cu-tolerant cotton cultivars that can be utilized for the phytoremediation of Cu-contaminated soils.

Monkeypox (MPOX) is a zoonotic viral disease caused by the Monkeypox virus (MPXV), which has become the most significant public health threat within the Orthopoxvirus genus since the eradication of the Variola virus (VARV). Despite the extensive attention MPXV has garnered, little is known about its clinical manifestations in humans. In this study, a high-throughput RNA sequencing (RNA-seq) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) approach was employed to investigate the transcriptional and metabolic responses of HEK293T cells to the MPXV A5L protein. RNA-seq analysis identified a total of 1473 differentially expressed genes (DEGs), comprising 911 upregulated and 562 downregulated genes. Additionally, LC-MS/MS analysis revealed 185 cellular proteins with significantly altered abundance ratios that interact with the A5L protein. Here, we perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of the transcriptome and proteome signatures of MPXV A5L-expressing HEK293T cells to gain insights into the virus proteins-host interplay. Transcriptomic analysis revealed that transfection of the MPXV A5L protein modulated genes primarily associated with the cell cycle, ribosome, and DNA replication. Proteomic analysis indicated that this protein predominantly interacted with host ribosomal proteins and cytoskeletal proteins. The combination of transcriptomic and proteomic analysis offers new perspectives for understanding the interaction between pathogens and hosts. Our research emphasizes the significant role of MPXV A5L in facilitating viral internalization and assembly, as well as its impact on the host’s translation system.

P addition increased rates of net N mineralization and ammonification but not nitrification. P addition increased soil bacterial biomass, but did not change fungi biomass. Soil enzymatic stoichiometry and microbial P limitation were responsible for N mineralization. The soil nitrogen (N) supply plays a core role in nutrient cycling, whereas phosphorus (P) is generally considered the limiting element of ecological processes in subtropical forests. However, the specific characteristics and regulatory mechanisms governing how P affects soil N mineralization remain incompletely understood. P fertilizer is often applied in bamboo forests, and we collected bulk soil and two types of rhizosphere soils (soils surrounding stump roots and rhizome roots, respectively) from a bamboo forest and conducted microcosm experiments with P addition (PA) to simulate the application of P fertilizer. The N mineralization and microbial and enzymatic parameters of the rhizosphere and bulk soils presented the same response to PA. PA increased the rate of net N mineralization and ammonification, suggesting that PA is beneficial to the N supply in the soil. PA increased the soil bacterial biomass but decreased the fungi:bacteria ratio. The soil enzyme C:N:P ratio indicated that the microbial community was subjected to P limitation. PA resulted in an increase in the enzyme C:P and N:P ratios and a decrease in the enzyme vector angle, suggesting alleviation of P limitation in the soil microbial community. Hierarchical partitioning and Pearson correlation analyses revealed that enzymatic stoichiometry and the vector angle were key regulators of soil N mineralization. These results indicate that PA can not only increase the concentration of soil P but also enhance the soil N supply in subtropical P-limited forests, primarily through changes in microbial nutrient limitation rather than in microbial biomass or community structure.

Rising atmospheric CO2 generally increases yield of indica rice, one of the two main Asian cultivated rice subspecies, more strongly than japonica rice, the other main subspecies. The molecular mechanisms driving this difference remain unclear, limiting the potential of future rice yield increases through breeding efforts. Here, we show that between-species variation in the DNR1 (DULL NITROGEN RESPONSE1) allele, a regulator of nitrate-use efficiency in rice plants, explains the divergent response to elevated atmospheric CO2 (eCO2) conditions. eCO2 increased rice yield by 22.8–32.3% in plants carrying or mimicking the indica DNR1 allele, but only by 3.6–11.1% in plants carrying the japonica DNR1 allele. Rice plants carrying or mimicking the indica DNR1 allele exhibit decreased eCO2-responsive transcription and protein abundance of DNR1, which activates genes involved in nitrate transport and assimilation, driving the increase in plant growth. Our findings identify the indica DNR1 gene as a key breeding resource for sustainably enhancing nitrate uptake and rice yields in japonica varieties, potentially contributing to global food security as atmospheric CO2 levels continue to increase.

Abamectin is an insecticide, miticide and nematicide that has been extensively used in agriculture for many years. The excessive use of abamectin inevitably pollutes water and soil and might even cause adverse effects on aquatic biota. However, it is currently unclear how abamectin exposure causes neurotoxicity in aquatic organisms. Herein, the early neural system development was assessed in zebrafish embryos following abamectin exposure. After treatment with a concentration gradient of abamectin (0.055, 0.0825, 0.11 mg/L), the survival rate, average heart rate, pericardial edema area and yolk sac edema were all documented in zebrafish embryos (96 hpf). It was found that after abamectin exposure, embryonic brain development was impaired, and motor behaviors were also affected. The fluorescence intensity was reduced in the transgenic embryos (Eno2: GFP). The activities of acetylcholinesterase (AChE) and ATPase were decreased, and the expression of neurodevelopment-related genes, such as sox10, gap43, grin1b, abat, gad1b, grin2b, nestin and glsa, were all inhibited in zebrafish embryo treatment with abamectin. Furthermore, the reactive oxygen species (ROS) were triggered upon exposure to abamectin in zebrafish embryos along with the accumulation of ROS, eventually resulting in neuroapoptosis in the developing embryonic brain. In conclusion, neurodevelopmental toxicity was caused by oxidative stress-induced apoptosis in zebrafish embryos following abamectin exposure.