Search Results (31)

In this study, a pH-responsive nanophotosensitizer (MT@Ce6) was rationally developed by strategic integration of MIL-101 (Fe)-NH₂ metal–organic framework with tannic acid (TA) and chlorin e6. This nanocomposite exhibits pH-responsive degradation in acidic microenvironments, facilitating Fe³⁺ release and subsequent reduction to Fe²⁺ that catalyzes Fenton reaction-mediated hydroxyl radical (•OH) generation. This cascade reaction shifts reactive oxygen species (ROS) predominance from transient singlet oxygen (¹O₂) to the long-range penetrative •OH, achieving robust biofilm disruption and over 90% eradication of methicillin-resistant Staphylococcus aureus (MRSA) under 660 nm irradiation. In vivo evaluations revealed accelerated wound healing with 95% wound closure within 7 days, while species-selective antibacterial studies demonstrated a 2.3-fold enhanced potency against Gram-positive bacteria due to their unique peptidoglycan-rich cell wall architecture. These findings collectively establish a microenvironment-adaptive nanoplatform for precision antimicrobial interventions, providing a translational strategy to address drug-resistant infections. Full article

Foxtail millet is a characteristic miscellaneous grain crop with many benefits in current agricultural production and is crucial in the adjustment of the planting structure and the sustainable development of dry farming. However, the harmful effects of weeds have become a critical challenge, restricting the modern production of foxtail millet. The effect of penoxsulam on the chlorophyll metabolism pathway of foxtail millet and its physiological mechanism was studied. Spraying penoxsulam on foxtail millet leaves significantly reduced the content of chlorophyll synthesis precursors (5-aminolevulinic acid (ALA), Porphobilinogen (PBG), Protoporphyrin IX (ProtoIX), Mg-protoporphyrin IX (Mg-ProtoIX), and Protochlorophyllide (Pchlide)). Moreover, the activities of key synthetic enzymes (magnesium chelatase (MgCh) decreased compared to control, while the activities of degrading enzymes (pheophorbide a oxygenase (PAO) and pheophytinase activities (PPH) increased significantly. The study revealed the mechanism of penoxsulam inducing crop phytotoxicity by interfering with the dynamic balance of chlorophyll metabolism, which provided a theoretical basis for the scientific application of herbicides and the study of foxtail millet drug resistance. Full article

Impeded by the limited light penetration of photodynamic therapy (PDT) to tissues and the hypoxic environment of solid tumors, the clinical therapeutic efficacy and application are below expectations. In this study, a glutathione (GSH)-responsive nano-photosensitizer, based on the chlorquinaldol (CQD)-loaded iron-containing nanorod composed of meso-tetra (4-carboxyphenyl) porphyrin (TCPP), was prepared to serve as the laser-ignited ferroptosis sensitizer to improve the tumoricidal effect of PDT. In the tumor microenvironment (TME) with elevated GSH levels, therapeutic cargos and ferrous ions are released and are accompanied by the degradation of the nano-photosensitizer and GSH exhaustion. This not only increases liable iron pool (LIP) accumulation by the released ferrous ions but also decreases glutathione peroxidase 4 (GPX4) activity by GSH exhaustion. Simultaneously, GSH exhaustion disrupts intracellular redox homeostasis, heightening NIR light irradiation-triggered photosensitive oxidative stress. Moreover, the released CQD elevates the level of intracellular reactive oxygen species (ROS), enabling the nanorods to gain an oxygen radical generation ability and enhancing the photosensitive oxidative therapeutic efficacy. Strikingly, CQD exacerbates the downregulation of GPX4 expression to promote the accumulation of lipid peroxides. Therefore, we herald a new paradigm for synergistically potentiating PDT based on the “all-in-one” nano-photosensitizer through the multi-pronged upregulation of ferroptosis sensitivity. Full article

Background: Activated hepatic stellate cells (aHSCs) play a significant role during the onset of hepatic fibrosis, ultimately leading to excessive deposition of extracellular matrix (ECM) and other typical pathological features, and thus have become a popular target for the treatment of hepatic fibrosis. However, current aHSC-centric therapy strategies achieve unsatisfactory results, mainly due to the lack of approved anti-fibrosis drugs and sufficiently efficient aHSC-targeted delivery systems. In this study, our aim was to develop an Imatinib-loaded nanoparticle delivery system based on a chondroitin sulfate derivative to enhance aHSC targeting efficiency, improve the therapeutic effect for hepatic fibrosis, and investigate the underlying mechanism. Methods: The carboxyl group of chondroitin sulfate and the amino group of 1-hexadecylamine were linked by an amide bond in this study to produce the amphiphilic carrier CS-HDA. Then, the Imatinib-loaded nanoparticles (IM-CS NPs) were designed to efficiently target aHSCs through CD44-mediated endocytosis and effectively inhibit HSC overactivation via PDGF and TGF-β signaling pathways. Results: Both in vitro cellular uptake experiments and in vivo distribution experiments demonstrated that CS-HDA-modified nanoparticles (IM-CS NPs) exhibited a better targeting ability for aHSCs, which were subsequently utilized to treat carbon tetrachloride-induced hepatic fibrosis mouse models. Finally, significant fibrosis resolution was observed in the carbon tetrachloride-induced hepatic fibrosis mouse models after tail vein injection of the IM-CS NPs, along with their outstanding biocompatibility and biological safety. Conclusions: IM-loaded NPs based on an amphiphilic CS derivative have remarkable antifibrotic effects, providing a promising avenue for the clinical treatment of advanced hepatic fibrosis. Full article

Macrophages play important roles in metabolic dysfunction-associated steatohepatitis (MASH), an advanced and inflammatory stage of metabolic dysfunction-associated steatotic liver disease (MASLD). In humans and mice, the cellular heterogeneity and diverse function of hepatic macrophages in MASH have been investigated by single cell RNA sequencing (scRNA-seq). However, little is known about their roles in rats. Here, we collected liver tissues at the postnatal week 16, when our previously characterized Lep^{∆I14/∆I14} rats developed MASH phenotypes. By scRNA-seq, we found an increase in the number of macrophages and endothelial cells and a decrease in that of NK and B cells. Hepatic macrophages in rats underwent a unique M1 to M2 transition without expression of the classical markers such as Arg1 and Nos2, except for Cd163. Lipid-associated macrophages (LAMs) were increased, which could be detected by the antibody against Cd63. In the microenvironment, macrophages had an increased number of interactions with hepatocytes, myofibroblasts, T cells, neutrophils, and dendritic cells, while their interaction strengths remained unchanged. Finally, the macrophage migration inhibitory factor (MIF) pathway was identified as the top upregulated cell-communication pathway in MASH. In conclusion, we dissected hepatic macrophage dynamics during MASH at single cell resolution and provided fundamental tools for the investigation of MASH in rat models. Full article

This paper addresses the issue of pesticide waste and low utilization rates resulting from traditional plant protection via spraying operations, which apply equal dosages to different targets or to different parts of the same target. To tackle this problem, we designed a variable fruit tree spraying system based on the ExG-AABB (excess green and axis-aligned bounding box) algorithm. We used a Kinect depth camera to capture information about the fruit tree canopy and constructed a spray flow model using pulse width modulation and variable spray control technology. Variable multi-nozzle spraying was guided by combining this canopy data. We evaluated the accuracy of each model in calculating canopy volume by comparing the coefficient of determination (R²) and root mean square error (RMSE) of the ExG-AABB with the slice convex hull method, voxel method, three-dimensional alpha-shape method, and QuickHull method. The ExG-AABB algorithm had the highest R² value (0.9334) and the lowest RMSE value (0.0353 m³) among the five models, indicating that it most accurately reflects the true volume of the fruit tree canopy. This validates the effectiveness of the ExG-AABB algorithm in calculating canopy volume. We established a correlation model between canopy volume and spray volume, designed a canopy-adaptive layering method based on point cloud processing, and achieved precise calculation of nozzle flow. Comparative field experiments were conducted to analyze the spray coverage rate and observed flow, thereby evaluating the spraying effect of this variable spraying system. The experimental results showed that compared to conventional continuous spraying, this variable spraying system not only achieves more uniform spray coverage but also significantly reduces pesticide usage by 48.1%. Furthermore, through system optimization, the average coverage rate of the middle layer of the canopy decreased by 17.53%, effectively reducing the phenomenon of overlapping spraying from multiple nozzles and improving spraying efficiency. Full article

Water extraction from synthetic aperture radar (SAR) images has an important application value in wetland monitoring, flood monitoring, etc. However, it still faces the problems of low generalization, weak extraction ability of detailed information, and weak suppression of background noises. Therefore, a new framework, Multi-scale Attention Detailed Feature fusion Network (MADF-Net), is proposed in this paper. It comprises an encoder and a decoder. In the encoder, ResNet101 is used as a solid backbone network to capture four feature levels at different depths, and then the proposed Deep Pyramid Pool (DAPP) module is used to perform multi-scale pooling operations, which ensure that key water features can be captured even in complex backgrounds. In the decoder, a Channel Spatial Attention Module (CSAM) is proposed, which focuses on feature areas that are critical for the identification of water edges by fusing attention weights in channel and spatial dimensions. Finally, the high-level semantic information is effectively fused with the low-level edge features to achieve the final water detection results. In the experiment, Sentinel-1 SAR images of three scenes with different characteristics and scales of water body are used. The PA and IoU of water extraction by MADF-Net can reach 92.77% and 89.03%, respectively, which obviously outperform several other networks. MADF-Net carries out water extraction with high precision from SAR images with different backgrounds, which could also be used for the segmentation and classification of other tasks from SAR images. Full article

The SAR system possesses the ability to carry out all-day and all-weather imaging, which is highly valuable in the application of aircraft identification. However, aircraft identification from SAR images still faces great challenges due to speckle noise interference, multiscale problems, and complex background interference. To solve these problems, an efficient bidirectional path multiscale fusion and attention network (EBMA-Net) is proposed in this paper. It employs bidirectional connectivity to fuse the features of aircraft with different scales to perform the accurate detection of aircraft even when the background is highly complex. In the presented EBMA-Net, a module called efficient multiscale channel attention fusion (EMCA) and three parallel squeeze efficient channel attention (SECA) modules are proposed. In the EMCA module, the bidirectional paths are created by stacking upper and lower fusion modules, which effectively integrate shallow detailed features and deep semantic information. So, the detection performance of aircraft at different scales is improved. In the SECA module, the dependency relationship between feature channels is explicitly modeled, which can automatically learn the importance of different channels, prioritize key features, so as to improve the precision and robustness of aircraft identification. In the experiment, the public dataset of aircraft identification (i.e., SAR-AIRcraft-1.0, which is generated from the GF-3 satellite) from high-resolution SAR systems is used, and several other excellent target-detection networks are used for performance comparison, namely, YOLOv5s, YOLOv7, MGCAN, and EBPA2N. According to the results, the average aircraft detection accuracy of EBMA-Net is 91.31%, which is 4.5% higher than YOLOv7; and the false alarm rate is decreased by 5%. Its accuracy in the identification of aircraft can reach 95.6%, which is about 3.7% higher than YOLOv7. Therefore, the EBMA-Net obviously outperforms the other networks for aircraft detection and identification. The proposed EBMA-Net, which can capture the detailed information and better restrain the background interference, could also be used to perform the detection and identification of dense targets with different scales and background from SAR images. Full article

Accurate estimation of surface evapotranspiration (ET) in the Heihe River Basin using remote sensing data is crucial for understanding water dynamics in arid regions. In this paper, by coupling physical constraints and machine learning for hybrid modeling, we develop a hybrid model based on surface conductance optimization. A hybrid modeling algorithm, two physical process-based ET algorithms (Penman–Monteith-based and Priestley–Taylor-based ET algorithms), and three pure machine learning algorithms (Random Forest, Extreme Gradient Boosting, and K Nearest Neighbors) are comparatively analyzed for estimating the ET. The results showed that, in general, the machine learning model optimized by parameters was able to better predict the surface conductance of the hybrid model. Driver analyses showed that radiation, normalized difference vegetation index (NDVI), and air temperature had high correlations with ET. The hybrid model had a better prediction performance for ET than the other five models, and it improved the R₂ of the two physical process-based algorithms to 0.9, reduced the root mean square error (RMSE) to 0.5 mm/day, reduced the BIAS to 0.2 mm/day, and improved the Kling–Gupta efficiency (KGE) to 0.9. The hybrid model outperformed the others across different time scales, displaying lower BIAS, RMSE, and higher KGE. Spatially, its ET patterns aligned with regional vegetation changes, with superior accuracy in annual ET estimation compared to the other models. Comparison with other ET products shows that the estimation results based on the hybrid model have better performance. This approach not only improves the accuracy of ET estimation but also improves the understanding of the physical mechanism of ET estimation by pure machine learning models. This study can provide important support for understanding ET and hydrological processes under different climatic and biotic vegetation in other arid and semi-arid regions. Full article

Pollen cells require large amounts of sugars from the anther to support their development, which is critical for plant sexual reproduction and crop yield. Sugars Will Eventually be Exported Transporters (SWEETs) have been shown to play an important role in the apoplasmic unloading of sugars from anther tissues into symplasmically isolated developing pollen cells and thereby affect the sugar supply for pollen development. However, among the 17 CsSWEET genes identified in the cucumber (Cucumis sativus L.) genome, the CsSWEET gene involved in this process has not been identified. Here, a member of the SWEET gene family, CsSWEET5a, was identified and characterized. The quantitative real-time PCR and β-glucuronidase expression analysis revealed that CsSWEET5a is highly expressed in the anthers and pollen cells of male cucumber flowers from the microsporocyte stage (stage 9) to the mature pollen stage (stage 12). Its subcellular localization indicated that the CsSWEET5a protein is localized to the plasma membrane. The heterologous expression assays in yeast demonstrated that CsSWEET5a encodes a hexose transporter that can complement both glucose and fructose transport deficiencies. CsSWEET5a can significantly rescue the pollen viability and fertility of atsweet8 mutant Arabidopsis plants. The possible role of CsSWEET5a in supplying hexose to developing pollen cells via the apoplast is also discussed. Full article

The contactless transmission between the conductor rotor and the permanent magnet (PM) rotor of an adjustable permanent magnet coupler (APMC) provides the device with significant tolerance for alignment errors, making the performance estimation complicated and inaccurate. The first proposal of an edge coefficient in this paper helps to describe the edge effect with better accuracy. Accurate equivalent magnetic circuit (EMC) models of the APMC are established for each region. Models of magnetic flux, magnetic resistance, and eddy current density are established by defining the equivalent dimensional parameters of the eddy current circuit. Furthermore, the concept of magnetic inductance is proposed for the first time, parameterizing eddy currents that are difficult to describe with physical models and achieving the modeling of the dynamic eddy current circuit. The magnetic resistance is subdivided into two parts corresponding to the output and slip according to the power relationship. Furthermore, eddy current loss and dynamic torque models are further derived. The method proposed in this paper enables the APMC to be modeled and calculated in a completely new way. The correctness and accuracy of the model have been fully demonstrated using finite element simulation and an experimental prototype. In addition, the limitations of the proposed method and the reasons are fully discussed and investigated. Full article

Accurate retrieval of ice surface temperature (IST) over the Arctic ice-water mixture zone (IWMZ) is significantly essential for monitoring the change of the polar sea ice environment. Previous researchers have focused on evaluating the accuracy of IST retrieval in pack ice regions, possibly on account of the availability of in situ measurement data. Few of them have assessed the accuracy of IST retrieval on IWMZ. This study utilized Landsat 8/TIRS and Operation IceBridge observations (OIB) to evaluate the accuracy of the current IST retrieval method in IWMZ and proposed an adjustment method for improving the overall accuracy. An initial comparison shows that Landsat 8 IST and OIB IST have minor differences in the pack ice region with RMSE of 0.475 K, MAE of 0.370 K and cold bias of −0.256 K. In the thin ice region, however, the differences are more significant, with RMSE of 0.952 K, MAE of 0.776 K and warm bias of 0.703 K. We suggest that this phenomenon is because the current ice-water classification method misclassified thin ice as water. To address this issue, an adjusted method is proposed to refine the classification of features within the IWMZ and thus improve the accuracy of IST retrieval using Landsat 8 imagery. The results demonstrate that the accuracy of the retrieved IST in the two cases was improved in the thin ice region, with RMSE decreasing by about 0.146 K, Bias decreasing by about 0.311 K, and MAE decreasing by about 0.129 K. After the adjustment, high accuracy was achieved for both pack ice and thin ice in IWMZ. Full article

One-step fermentation, inoculated with Lactobacillus fermentum (L. fermentum) in shrimp by-products, was carried out to obtain chitin and flavor protein hydrolysates at the same time. The fermentation conditions were optimized using response surface methodology, resulting in chitin with a demineralization rate of 89.48%, a deproteinization rate of 85.11%, and a chitin yield of 16.3%. The surface of chitin after fermentation was shown to be not dense, and there were a lot of pores. According to Fourier transform infrared spectroscopy and X-ray diffraction patterns, the fermented chitin belonged to α-chitin. More than 60 volatiles were identified from the fermentation broth after chitin extraction using gas chromatography–ion transfer spectrometry analysis. L. fermentum fermentation decreased the intensities of volatile compounds related to unsaturated fatty acid oxidation or amino acid deamination. By contrast, much more pleasant flavors related to fruity and roasted aroma were all enhanced in the fermentation broth. Our results suggest an efficient one-step fermentation technique to recover chitin and to increase aroma and flavor constituents from shrimp by-products. Full article

Plastic electrodes are desirable for the rapid development of flexible organic electronics. In this article, a plastic electrode has been prepared by employing traditional conducting polymer poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) and plastic substrate polyethersulfone (PES). The completed electrode (Denote as HC-PEDOT:PSS) treated by 80% concentrated sulfuric acid (H₂SO₄) possesses a high electrical conductivity of over 2673 S/cm and a high transmittance of over 90% at 550 nm. The high conductivity is attributed to the regular arrangement of PEDOT molecules, which has been proved by the X-ray diffraction characterization. Temperature-dependent conductivity measurement reveals that the HC-PEDOT:PSS possesses both semiconducting and metallic properties. The binding force and effects between the PEDOT and PEI are investigated in detail. All plastic solar cells with a classical device structure of PES/HC-PEDOT:PSS/PEI/P3HT:ICBA/EG-PEDOT:PSS show a PCE of 4.05%. The ITO-free device with a structure of Glass/HC-PEDOT:PSS/Al4083/PM6:Y6/PDINO/Ag delivers an open-circuit voltage (V_OC) of 0.81 V, short-circuit current (J_SC ) of 23.5 mA/cm², fill factor (FF) of 0.67 and a moderate power conversion efficiency (PCE) of 12.8%. The above results demonstrate the HC-PEDOT:PSS electrode is a promising candidate for all-plastic solar cells and ITO-free organic solar cells. Full article

Smoke image segmentation plays a vital role in the accuracy of target extraction. In order to improve the performance of the traditional fire image segmentation algorithm, a new smoke segmentation method based on improved double truncation distance self-adaptive density peak clustering(TSDPC) is proposed. Firstly, the smoke image is over-segmented into multiple superpixels to reduce the time cost, and the local density of sample points corresponding to each superpixel is redefined by location information and color space information. Secondly, TSDPC combines the information entropy theory to find the optimal double truncation distance. Finally, TSDPC uses trigonometric functions to determine clustering centers in the decision diagram, which can solve the problem of over-segmentation. Then, it assigns labels to the remain sample points for obtaining the clustering result. Compared with other algorithms, the accuracy of TSDPC is increased by 5.68% on average, and the $F_1$ value is increased by 6.69% on average, which shows its high accuracy and effectiveness. In public dataset, TSDPC has also demonstrated its effectiveness. Full article