Search Results (18)

Cotton leaf diseases can lead to substantial yield losses and economic burdens. Traditional detection methods are challenged by low accuracy and high labor costs. This research presents the ACURS-YOLO network, an advanced cotton leaf disease detection architecture developed on the foundation of YOLOv11. By integrating a medical image segmentation model, it effectively tackles challenges including complex background interference, the missed detection of small targets, and restricted generalization ability. Specifically, the U-Net v2 module is embedded in the backbone network to boost the multi-scale feature extraction performance in YOLOv11. Meanwhile, the CBAM attention mechanism is integrated to emphasize critical disease-related features. To lower the computational complexity, the SPPF module is substituted with SimSPPF. The C3k2_RCM module is appended for long–range context modeling, and the ARelu activation function is employed to alleviate the vanishing gradient problem. A database comprising 3000 images covering six types of cotton leaf diseases was constructed, and data augmentation techniques were applied. The experimental results show that ACURS-YOLO attains impressive performance indicators, encompassing a mAP_0.5 value of 94.6%, a mAP_0.5:0.95 value of 83.4%, 95.5% accuracy, 89.3% recall, an F1 score of 92.3%, and a frame rate of 148 frames per second. It outperforms YOLOv11 and other conventional models with regard to both detection precision and overall functionality. Ablation tests additionally validate the efficacy of each component, affirming the framework’s advantage in addressing complex detection environments. This framework provides an efficient solution for the automated monitoring of cotton leaf diseases, advancing the development of smart sensors through improved detection accuracy and practical applicability. Full article

Maintenance hemodialysis patients are at increased risk of cardiovascular complications and mortality following COVID-19 infection due to compromised immune function. This study aims to evaluate the impact of the COVID-19 vaccine (CoronaVac) on cardiac function and survival in this population. Background/Objectives: We aimed to examine whether CoronaVac vaccination affects heart function and survival rates in maintenance hemodialysis patients. Specifically, we assessed changes in heart ultrasound (echocardiographic) measurements, B-type natriuretic peptide (BNP) levels, and survival outcomes by comparing vaccinated and unvaccinated patients. Methods: A retrospective analysis was conducted on 531 maintenance hemodialysis patients, including 79 who received CoronaVac and 452 who did not. We compared the pre- and post-infection changes in heart function (echocardiographic parameters) and BNP levels between the two groups and assessed their association with the survival rates. Results: The vaccinated patients were younger (60.54  ±  13.51 vs. 65.21  ±  13.76 years, p = 0.006) and had shorter dialysis durations (56.04  ±  51.88 vs. 73.73  ±  64.79 months, p = 0.022). The mortality rate was also significantly lower in the vaccinated group (6.33% vs. 14.38%, p = 0.049). After infection, the unvaccinated patients showed significant declines in heart function and increased B-type natriuretic peptide levels, while the vaccinated patients demonstrated no significant deterioration. Older age, coronary artery disease, inflammation levels, and heart abnormalities were identified as the key risk factors for mortality. Conclusions: CoronaVac was linked to lower mortality and better heart function in maintenance hemodialysis patients. The vaccine may help to reduce infection severity, lower strain on the heart, and improve the overall prognosis. Full article

Chlorophyll is crucial for pear tree growth and fruit quality. In order to integrate the unmanned aerial vehicle (UAV) multispectral vegetation indices and textural features to realize the estimation of the SPAD value of pear leaves, this study used the UAV multispectral remote sensing images and ground measurements to extract the vegetation indices and textural features, and analyze their correlation with the SPAD value of leaves during the fruit expansion period of the pear tree. Finally, four machine learning methods, namely XGBoost, random forest (RF), back-propagation neural network (BPNN), and optimized integration algorithm (OIA), were used to construct inversion models of the SPAD value of pear trees, with different feature inputs based on vegetation indices, textural features, and their combinations, respectively. Moreover, the differences among these models were compared. The results showed the following: (1) both vegetation indices and textural features were significantly correlated with SPAD values, which were important indicators for estimating the SPAD values of pear leaves; (2) combining vegetation indices and textural features significantly improved the accuracy of SPAD value estimation compared with a single feature type; (3) the four machine learning algorithms demonstrated good predictive ability, and the OIA model outperformed the single model, with the model based on the OIA inversion model combining vegetation indices and textural features having the best accuracy, with $R^2$ values of 0.931 and 0.877 for the training and validation sets, respectively. This study demonstrated the efficacy of integrating multiple models and features to accurately invert SPAD values, which, in turn, supported the refined management of pear orchards. Full article

Urban vitality is a critical driver of sustainable urban development, significantly contributing to the enhancement of human well-being. A thorough and multidimensional comprehension of urban vitality is essential for shaping future urban planning and policy-making. This study, focused on Chengdu, proposes a framework for assessing various dimensions of UV through the distribution of milk tea and coffee shops. Using random forest and multi-scale geographically weighted regression models, this study investigates the factors influencing urban vitality from both mathematical thresholds and spatial heterogeneity, and develops spatial maps of future vitality to inform targeted urban strategies. The results show that (1) the milk tea index is effective in capturing population vitality, while the coffee index is more closely associated with economic vitality and urban renewal; (2) office buildings (13.46%) and commercial complexes (13.70%) have the most significant impact on both economic and population vitality, while the importance of transportation factors has notably decreased; (3) the influence of these factors demonstrates spatial heterogeneity and nonlinear relationships, with subway station density of 0.5–0.8 stations per kilometer being optimal for stimulating both types of vitality. The minimum threshold for economic vitality in a given unit is a housing price exceeding 6000 RMB/m²; (4) the future vitality map suggests that urban planners should pay greater attention to non-central districts with high development potential. Moreover, spontaneous social interactions and consumer behaviors stimulated by various shops are critical components of urban vitality. In designing the physical environment and urban spatial forms, special attention should be given to enhancing the attractiveness of physical spaces and their capacity to accommodate social interaction. Full article

Traditional methods are unable to effectively assess the health status of engine bleed air systems. To address the limitation, this paper proposes a methodology for constructing health indicators using multi-level feature extraction. First, this approach involves data-level feature extraction from Quick Access Recorder (QAR) data and employs a method of significance compensation to process the QAR data. Second, through unsupervised learning, the ResNet Deep Autoencoder (RDAE) is utilized to do the feature-level feature extraction from the processed data. This can solve the problem of lacking annotated data and obtain the health indicators of the engine bleed air system. Third, the method was experimented on one year of QAR data from a specific airline company. The results demonstrate that the RDAE approach achieves the best performance in constructing health indicators for the system. It achieves a miss rate of 0.0523 for the duct pressure of 5th stage bleed, reducing the miss rate by 0.2810 compared to Kernel Principal Component Analysis (KPCA). It also achieves a miss rate of 0 for the pre-cooler outlet temperature, reducing the miss rate by 0.0035 compared to the Deep Autoencoder (DAE). The results indicate that the proposed method provides a more effective assessment of the health status of the engine bleed air system. Full article

The affinity of peptides is a crucial factor in studying peptide–protein interactions. Despite the development of various techniques to evaluate peptide–receptor affinity, the results may not always reflect the actual affinity of the peptides accurately. The current study provides a free tool to assess the actual peptide affinity based on virtual docking data. This study employed a dataset that combined actual peptide affinity information (active and inactive) and virtual peptide–receptor docking data, and different machine learning algorithms were utilized. Compared with the other algorithms, the random forest (RF) algorithm showed the best performance and was used in building three RF models using different numbers of significant features (four, three, and two). Further analysis revealed that the four-feature RF model achieved the highest Accuracy of 0.714 in classifying an independent unknown peptide dataset designed with the PEDV spike protein, and it also revealed overfitting problems in the other models. This four-feature RF model was used to evaluate peptide affinity by constructing the relationship between the actual affinity and the virtual docking scores of peptides to their receptors. Full article

R2R3-MYB TFs represent one of the most extensive gene families in plants and play a crucial role in regulating plant development, metabolite accumulation, and defense responses. Nevertheless, there has been no systematic investigation into the pomegranate R2R3-MYB family. In this study, 186 R2R3-MYB genes were identified from the pomegranate genome and grouped into 34 subgroups based on phylogenetic analysis. Gene structure analysis showed that the PgR2R3-MYB family in the same subgroup had a similar structure. Gene duplication event analysis revealed that the amplification of the PgMYB family was driven by Whole Genome Duplication (WGD) and dispersed duplication. In the upstream promoter sequence of the PgMYB gene, we identified a large number of plant hormones and environmental response elements. Using phylogenetic analysis and RNA-seq analysis, we identified three PgMYB TFs that may be involved in the regulation of lignin synthesis. Their expression patterns were verified by qPCR experiments. This study provides a solid foundation for further studies on the function of the R2R3-MYB gene and the molecular mechanism of lignin synthesis. Full article

Porcine epidemic diarrhea virus (PEDV) has led to significant economic losses in the global porcine industry since the emergence of variant strains in 2010. The high mutability of coronaviruses endows PEDV with the ability to evade the host immune response, which impairs the effectiveness of vaccines. In our previous study, we generated a highly cell-passaged PEDV strain, CT-P120, which showed promise as a live attenuated vaccine candidate by providing satisfactory protection against variant PEDV infection in piglets. However, the mechanism by which the attenuated CT-P120 adapts to cells during passage, resulting in increased replication efficiency, remains unclear. To address this question, we conducted a comparative transcriptomic analysis of Vero E6 cells infected with either the original parental strain (CT-P10) or the cell-attenuated strain (CT-P120) of PEDV at 6, 12, and 24 h post-infection. Compared to CT-P10, CT-P120 infection resulted in a significant decrease in the number of differentially expressed genes (DEGs) at each time point. Functional enrichment analysis of genes revealed the activation of various innate immune-related pathways by CT-P10, notably attenuated during CT-P120 infection. To validate these results, we selected eight genes (TRAF3, IRF3, IFNL1, ISG15, NFKB1, MAP2K3, IL1A, and CCL2) involved in antiviral processes and confirmed their mRNA expression patterns using RT-qPCR, in line with the transcriptomic data. Subsequent protein-level analysis of selected genes via Western blotting and enzyme-linked immunosorbent assay corroborated these results, reinforcing the robustness of our findings. Collectively, our research elucidates the strategies underpinning PEDV attenuation and immune evasion, providing invaluable insights for the development of effective PEDV vaccines. Full article

Anthocyanidin Synthase (ANS) is a key enzyme in the later stages of the anthocyanin biosynthetic pathway, and its role is to convert colorless leucoanthocyanidins to colored anthocyanidins. In this study, a total of 75 members of the pomegranate ANS family were identified and divided into four groups (Group I, Group Ⅱ, Group Ⅲ and Group Ⅳ) based on evolutionary relationships. The 75 ANS gene family members were unevenly distributed on seven of the eight chromosomes of pomegranate. The results of the physical and chemical property analysis showed that 93.33% of the proteins were acidic proteins, 6.67% were alkaline proteins, 28% of the proteins were stable proteins and 72% were unstable proteins. Protein secondary structure analysis showed that α-Spiral and irregular curl are the main structural elements. Analysis of the conserved structural domains of the proteins showed that all 75 ANS family members contained one DIOX -N subfamily structural domain and one 2OG-FeII_Oxy subfamily structural domain. The results of subcellular localization showed that all 75 ANS family members of pomegranate were localized in the cytoplasm. Analysis of the transcriptome data showed that the expression of the pomegranate ANS genes were variety-specific and period-specific. Full article

Increasing shoot branch numbers of Chrysanthemum morifolium Ramat cv. Hangbaiju (Hangbaiju) is crucial for producing high flower yields. Pot experiments were designed to evaluate the effects of foliar application of 6-benzylaminopurine (6-BA) combined with prohexadione-Ca (Pro-Ca) on the yield and quality of Hangbaiju flowers. Foliar application of 6-BA combined with Pro-Ca typically increased leaf chlorophyll content and decreased leaf soluble sugar and soluble protein contents throughout the floral organ growth phase. At the bud formation phenophase stage (August), the contents of gibberellin (GA), indole-3-acetic acid (IAA), and zeatin (ZA) decreased (except for GA content in the 10 mg L⁻¹ 6-BA combined with 100 mg L⁻¹ Pro-Ca treatment), but abscisic acid (ABA) content increased. The yield of Hangbaiju flowers was found higher in plants treated with foliar application of 6-BA combined with Pro-Ca. Higher yields were found in the 6-BA₅ + Ca₁₀₀ and 6-BA₁₀ + Ca₁₀₀ treatments than in the 6-BA₅ + Ca₅₀ and 6-BA₁₀ + Ca₅₀ treatments, and the highest yield was observed in the 6-Ba₅ + Ca₁₀₀ treatment both in 2019 and 2020. Nutritional indices such as soluble sugar, soluble protein, total amino acid, and water extract increased, and medicinal indices such as flavonoid, total phenolics, chlorogenic acid, cynaroside, and 3,5-dicaffeoyl quinic acid slightly decreased after foliar application of 6-BA combined with Pro-Ca; however, they were all higher than the standards recorded in the Chinese Pharmacopeia. Overall, foliar application of 6-BA combined with Pro-Ca could increase the yield and nutritional quality of Hangbaiju flowers, enhancing its tea quality. Full article

Due to the rapid mutation of porcine epidemic diarrhea virus (PEDV), existing vaccines cannot provide sufficient immune protection for pigs. Therefore, it is urgent to design the affinity peptides for the prevention and control of this disease. In this study, we made use of a molecular docking technology for virtual screening of affinity peptides that specifically recognized the PEDV S1 C-terminal domain (CTD) protein for the first time. Experimentally, the affinity, cross-reactivity and sensitivity of the peptides were identified by an enzyme-linked immunosorbent assay (ELISA) and a surface plasmon resonance (SPR) test, separately. Subsequently, Cell Counting Kit-8 (CCK-8), quantitative real-time PCR (qRT-PCR), Western blot and indirect immunofluorescence were used to further study the antiviral effect of different concentrations of peptide 110766 in PEDV. Our results showed that the P/N value of peptide 110766 at 450 nm reached 167, with a K_D value of 216 nM. The cytotoxic test indicated that peptide 110766 was not toxic to vero cells. Results of the absolute quantitative PCR revealed that different concentrations (3.125 μM, 6.25 μM, 12.5 μM, 25 μM, 50 μM, 100 μM, 200 μM) of peptide 110766 could significantly reduce the viral load of PEDV compared with the virus group (p < 0.0001). Similarly, results of Western blot and indirect immunofluorescence also suggested that the antiviral effect of peptide 110766 at 3.125 is still significant. Based on the above research, high-affinity peptide 110766 binding to the PEDV S1-CTD protein was attained by a molecular docking technology. Therefore, designing, screening, and identifying affinity peptides can provide a new method for the development of antiviral drugs for PEDV. Full article

[Objective] Cinnamyl alcohol dehydrogenase (CAD) is a key enzyme in lignin biosynthesis. The aim of this study was to identify CAD gene family members in pomegranate and its expression correlation with seed hardness. [Methods] Based on the reported CAD sequence of Arabidopsis, the CAD gene family of pomegranate was identified by homologous comparison, and then phylogenetic, molecular characterization, and expression profile analysis were performed. [Results] Pomegranate CAD gene family has 25 members, distributed on seven chromosomes of pomegranate. All pomegranate CAD proteins have similar physical and chemical properties. We divide the family into four groups based on evolutionary relationships. The member of group I, called bona fide CAD, was involved in lignin synthesis. Most of the members of group II were involved in stress resistance. The functions of groups III and IV need to be explored. We found four duplicated modes (whole genome duplication or segmental (WGD), tandem duplication (TD), dispersed duplication (DSD), proximal duplication (PD) in this family; TD (36%) had the largest number of them. We predicted that 20 cis-acting elements were involved in lignin synthesis, stress resistance, and response to various hormones. Gene expression profiles further demonstrated that the PgCAD gene family had multiple functions. [Conclusions] Pomegranate CAD gene family is involved in lignin synthesis of hard-seeded cultivar Hongyushizi and Baiyushizi, but its role in seed hardness of soft-seeded cultivar Tunisia needs to be further studied. Full article

Changes in the proportions of male and female flowers in monoecious plants in response to external environmental conditions are directly related to the reproductive fitness of plants. The monoecious cucumber (Cucumber sativus) plant was used in this study to assess the responses of sex differentiation and the breeding process to nutrient supply and the degree of artificial pollination using pollen solutions of different concentrations. We found that the nutrient supply significantly improved the number of female flowers, while pollination treatments did not obviously increase the number of male flowers. Continuous pollination changed the number of female flowers especially in the later stage of the pollination experiment. Therefore, pollination changed the ratio of male and female flowers in the flowering stage of cucumber. Pollination treatment affected the fruit growth, seed set, and fruit yield. The number of fruit, fruit set percentage, and total seeds per plant did not increase with the pollination level, but individual fruit weight and seed number in one fruit did increase. The differentiation of male and female flowers in the flowering stage of cucumber is a response to nutrient and pollination resources, but this response is not the optimal resource allocation for subsequent fruit development and seed maturity, which suggests that the response of plants to external environment resources is short-term and direct. Full article

An immunized mouse phage display scFv library with a capacity of 3.34 × 10⁹ CFU/mL was constructed and used for screening of recombinant anti-ciprofloxacin single-chain antibody for the detection of ciprofloxacin (CIP) in animal-derived food. After four rounds of bio-panning, 25 positives were isolated and identified successfully. The highest positive scFv-22 was expressed in E. coli BL21. Then, its recognition mechanisms were studied using the molecular docking method. The result showed the amino acid residue Val160 was the key residue for the binding of scFv to CIP. Based on the results of virtual mutation, the scFv antibody was evolved by directional mutagenesis of contact amino acid residue Val160 to Ser. After the expression and purification, an indirect competitive enzyme-linked immunosorbent assay (IC-ELISA) based on the parental and mutant scFv was established for CIP, respectively. The IC50 value of the assay established with the ScFv mutant was 1.58 ng/mL, while the parental scFv was 26.23 ng/mL; this result showed highly increased affinity, with up to 16.6-fold improved sensitivity. The mean recovery for CIP ranged from 73.80% to 123.35%, with 10.46% relative standard deviation between the intra-assay and the inter-assay. The RSD values ranged between 1.49% and 9.81%. The results indicate that we obtained a highly sensitive anti-CIP scFv by the phage library construction and directional evolution, and the scFv-based IC-ELISA is suitable for the detection of CIP residue in animal-derived edible tissues. Full article

Swine acute diarrhea syndrome coronavirus (SADS-CoV) is a newly emerged and highly pathogenic virus that is associated with fatal diarrhea disease in piglets, causing significant economic losses to the pig industry. At present, the research on the pathogenicity and molecular mechanisms of host-virus interactions of SADS-CoV are limited and remain poorly understood. Here, we investigated the global gene expression profiles of SADS-CoV-infected Vero E6 cells at 12, 18, and 24 h post-infection (hpi) using the RNA-sequencing. As a result, a total of 3324 differentially expressed genes (DEG) were identified, most of which showed a down-regulated expression pattern. Functional enrichment analyses indicated that the DEGs are mainly involved in signal transduction, cellular transcription, immune and inflammatory response, and autophagy. Collectively, our results provide insights into the changes in the cellular transcriptome during early infection of SADS-CoV and may provide information for further study of molecular mechanisms. Full article