Search Results (4)

Petal abscission affects the growth, development, and economic value of plants, but the mechanism of ethylene-ROS-induced petal abscission is not clear. Therefore, we treated roses with different treatments (MOCK, ETH, STS, and ETH + STS), and phenotypic characteristics of petal abscission, changed ratio of fresh weight, morphology of cells in AZ and the expression of RhSUC2 were analyzed. On this basis, we measured reactive oxygen species (ROS) content in petals and AZ cells of roses, and analyzed the expression levels of some genes related to ROS production and ROS scavenging. Ethylene promoted the petal abscission of rose through decreasing the fresh weight of the flower, promoting the stacking and stratification of AZ cells, and repressing the expression of RhSUC2. During this process, ethylene induced the ROS accumulation of AZ cells and petals mainly through increasing the expressions of some genes (RhRHS17, RhIDH1, RhIDH-III, RhERS, RhPBL32, RhFRS5, RhRAC5, RhRBOHD, RhRBOHC, and RhPLATZ9) related to ROS production and repressing those genes (RhCCR4, RhUBC30, RhSOD1, RhAPX6.1, and RhCATA) related to ROS scavenging. In summary, ROS and related regulatory factors involved in ethylene induced petal abscission in roses. Full article

Retrogressive thaw slumps (RTSs) are becoming more common on the Qinghai-Tibet Plateau as permafrost thaws, but the hydraulic properties of thaw slumps have not been extensively studied. To fill this knowledge gap, we used the “space-for-time substitution method” to differentiate three stages of RTSs: original grassland, collapsing, and collapsed. Our study included on-site investigations, measurements in the laboratory, and measured and simulated analyses of soil water retention curves and estimated hydrological properties. Our findings show that the measurements and simulated analyses of soil water retention were highly consistent across RTSs, indicating the accuracy of the Van Genuchten model in reproducing soil hydraulic parameters for different stages of RTSs. The original grassland stage had the highest soil water retention and content due to its high soil organic carbon (SOC) content and fine-textured micropores. In contrast, the collapsed stage had higher soil water retention and content compared to the collapsing stage, primarily due to increased proportions of soil micropores, SOC content, and lower bulk density (BD). From original grassland stage to collapsed stage, there were significant changes on the structure of each RTS site, which resulted in a decrease in SOC content and an increase in BD in general. However, the absence of soil structure and compaction led to the subsequent accumulation of organic matter, increasing SOC content. Changes in field capacity, permanent wilting point, and soil micropore distribution aligned with variations in SOC content and water content. These findings highlight the importance of managing SOC content and water content to mitigate the adverse effects of freeze-thaw cycles on soil structure and stability at different thaw collapse stages of RTSs. Effective management strategies may include incorporating organic matter, reducing soil compaction, and maintaining optimal water content. Further research is needed to determine the most suitable management practices for different soil types and environmental conditions. Full article

Rapid and accurate detection of changes in glucose (Glu) and hydrogen peroxide (H₂O₂) concentrations is essential for the predictive diagnosis of diseases. Electrochemical biosensors exhibiting high sensitivity, reliable selectivity, and rapid response provide an advantageous and promising solution. A porous two-dimensional conductive metal–organic framework (cMOF), Ni-HHTP (HHTP = 2,3,6,7,10,11-hexahydroxytriphenylene), was prepared by using a one-pot method. Subsequently, it was employed to construct enzyme-free paper-based electrochemical sensors by applying mass-producing screen-printing and inkjet-printing techniques. These sensors effectively determined Glu and H₂O₂ concentrations, achieving low limits of detection of 1.30 μM and 2.13 μM, and high sensitivities of 5573.21 μA μM⁻¹ cm⁻² and 179.85 μA μM⁻¹ cm⁻², respectively. More importantly, the Ni-HHTP-based electrochemical sensors showed an ability to analyze real biological samples by successfully distinguishing human serum from artificial sweat samples. This work provides a new perspective for the use of cMOFs in the field of enzyme-free electrochemical sensing, highlighting their potential for future applications in the design and development of new multifunctional and high-performance flexible electronic sensors. Full article

Deep learning (DL) is widely applied in the field of hyperspectral image (HSI) classification and has proved to be an extremely promising research technique. However, the deployment of DL-based HSI classification algorithms in mobile and embedded vision applications tends to be limited by massive parameters, high memory costs, and the complex networks of DL models. In this article, we propose a novel, extremely lightweight, non-deep parallel network (HyperLiteNet) to address these issues. Based on the development trends of hardware devices, the proposed HyperLiteNet replaces the deep network by the parallel structure in terms of fewer sequential computations and lower latency. The parallel structure can extract and optimize the diverse and divergent spatial and spectral features independently. Meanwhile, an elaborately designed feature-interaction module is constructed to acquire and fuse generalized abstract spectral and spatial features in different parallel layers. The lightweight dynamic convolution further compresses the memory of the network to realize flexible spatial feature extraction. Experiments on several real HSI datasets confirm that the proposed HyperLiteNet can efficiently decrease the number of parameters and the execution time as well as achieve better classification performance compared to several recent state-of-the-art algorithms. Full article