Explore the vast range of titles available.

Kiwifruit bacterial canker is a devastating disease threatening kiwifruit production. To clarify the defense mechanism in response to Pseudomonas syringae pv. actinidiae (Psa), we observed phenotypic changes in resistant Huate (HT) and susceptible Hongyang (HY) kiwifruit varieties at 0, 12, 24, 48, 96, and 144 hour after inoculation (hai) with Psa. Brown lesions appeared in the inoculation areas 12 hai in HY shoots, and the lesion length gradually increased from 24 to 144 h. In contrast, no lesions were found in HT shoots at any time points. Furthermore, RNA-seq analysis showed significantly more differentially expressed genes between HT and HY at 12 hai than at any other time point. According to weighted gene co-expression network analysis, five modules were notably differentially expressed between HT and HY; pathway mapping using the Kyoto Encyclopedia of Gene and Genomes database was performed for the five modules. In MEgreenyellow and MEyellow modules, pathways related to\"plant-pathogen interaction\", \"Endocytosis\", \"Glycine, serine and threonine metabolism\", and \"Carbon fixation in photosynthetic organisms\" were enriched, whereas in the MEblack module, pathways related to \"protein processing in endoplasmic reticulum\", \"plant-pathogen interaction\", and \"Glycolysis / Gluconeogenesis\" were enriched. In particular, the Pti1 and RPS2 encoding effector receptors, and the NPR1, TGA, and PR1 genes involved in the salicylic acid signaling pathway were significantly up-regulated in HT compared with HY. This indicates that the effector-triggered immunity response was stronger and that the salicylic acid signaling pathway played a pivotal role in the Psa defense response of HT. In addition, we identified other important genes, involved in phenylpropanoid biosynthesis and Ca2+ internal flow, which were highly expressed in HT. Taken together, these results provide important information to elucidate the defense mechanisms of kiwifruit during Psa infection.

Calcific aortic valve disease is a prevalent cardiovascular disease with no available drugs capable of effectively preventing its progression. Hence, an efficient drug delivery system could serve as a valuable tool in drug screening and potentially enhance therapeutic efficacy. However, due to the rapid blood flow rate associated with aortic valve stenosis and the lack of specific markers, achieving targeted drug delivery for calcific aortic valve disease has proved to be challenging. Here we find that protease-activated-receptor 2 (PAR2) expression is up-regulated on the plasma membrane of osteogenically differentiated valvular interstitial cells. Accordingly, we develop a magnetic nanocarrier functionalized with PAR2-targeting hexapeptide for dual-active targeting drug delivery. We show that the nanocarriers effectively deliver XCT790—an anti-calcification drug—to the calcified aortic valve under extra magnetic field navigation. We demonstrate that the nano-cargoes consequently inhibit the osteogenic differentiation of valvular interstitial cells, and alleviate aortic valve calcification and stenosis in a high-fat diet-fed low-density lipoprotein receptor-deficient ( Ldlr −/− ) mouse model. This work combining PAR2- and magnetic-targeting presents an effective targeted drug delivery system for treating calcific aortic valve disease in a murine model, promising future clinical translation. Achieving targeted drug delivery for calcified aortic valve is challenging. Here, the authors find that protease activated receptor 2 (PAR2) is up-regulated on calcified valves and develop a magnetic nanocarrier functionalized with PAR2-targeting peptide for dual-active drug delivery.

As one of the largest transcription factor family, basic helix-loop-helix (bHLH) transcription factor family plays an important role in plant metabolism, physiology and growth. Berry color is one of the important factors that determine grape quality. However, the bHLH transcription factor family’s function in anthocyanin synthesis of grape berry has not been studied systematically. We identified 115 bHLH transcription factors in grape genome and phylogenetic analysis indicated that bHLH family could be classified into 25 subfamilies. First, we screened six candidate genes by bioinformatics analysis and expression analysis. We found one of the candidate genes VdbHLH037 belonged to III (f) subfamily and interacted with genes related to anthocyanin synthesis through phylogenetic analysis and interaction network prediction. Therefore, we speculated that VdbHLH037 participated in the anthocyanin synthesis process. To confirm this, we transiently expressed VdbHLH037 in grape and Arabidopsis transformation. Compared with the control, transgenic materials can accumulate more anthocyanins. These results provide a good base to study the function of the VdbHLH family in anthocyanin synthesis of grape berry.

Cold stress poses a serious treat to cultivated kiwifruit since this plant generally has a weak ability to tolerate freezing tolerance temperatures. Surprisingly, however, the underlying mechanism of kiwifruit’s freezing tolerance remains largely unexplored and unknown, especially regarding the key pathways involved in conferring this key tolerance trait. Here, we studied the metabolome and transcriptome profiles of the freezing-tolerant genotype KL ( Actinidia arguta ) and freezing-sensitive genotype RB ( A. arguta ), to identify the main pathways and important metabolites related to their freezing tolerance. A total of 565 metabolites were detected by a wide-targeting metabolomics method. Under (−25°C) cold stress, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway annotations showed that the flavonoid metabolic pathways were specifically upregulated in KL, which increased its ability to scavenge for reactive oxygen species (ROS). The transcriptome changes identified in KL were accompanied by the specific upregulation of a codeinone reductase gene, a chalcone isomerase gene, and an anthocyanin 5-aromatic acyltransferase gene. Nucleotides metabolism and phenolic acids metabolism pathways were specifically upregulated in RB, which indicated that RB had a higher energy metabolism and weaker dormancy ability. Since the LPCs (LysoPC), LPEs (LysoPE) and free fatty acids were accumulated simultaneously in both genotypes, these could serve as biomarkers of cold-induced frost damages. These key metabolism components evidently participated in the regulation of freezing tolerance of both kiwifruit genotypes. In conclusion, the results of this study demonstrated the inherent differences in the composition and activity of metabolites between KL and RB under cold stress conditions.

In the field of low-altitude aerial drone data fusion, the fusion of infrared and visible light images remains challenging due to issues such as large modal differences, insufficient cross-modal alignment, and limited global context modeling. Traditional methods struggle to extract complementary information across modalities, while deep learning methods often lack sufficient global receptive fields (convolutional neural networks) or fail to preserve local details (standard Transformers). To address these issues, we propose a Cross-modal Guided Dual-Branch Network (CGDBN) that combines convolutional neural networks and Transformer architecture. Our framework contribution: We designed a Target-modal Feature Extraction Mechanism (TMFEM) module with specialized thermal characteristics for infrared feature extraction, which does not require processing of visible light features; we introduced Simplified Linear Attention Blocks (SLABs) into our framework to improve global context capture as a module; we designed a Cross-Modal Interaction Mechanism (CMIM) module for bidirectional feature interaction; and we designed a Density Adaptive Multimodal Fusion (DAMF) module that weights modal contributions based on content analysis. This asymmetric design recognizes that different types of images have different characteristics and require targeted processing. The experimental results on AVMS, M3FD, and TNO datasets show that the proposed model has a peak signal-to-noise ratio (PSNR) of 16.2497 on the AVMS dataset, which is 0.9971 higher than the best benchmark method YDTR (peak signal-to-noise ratio: approximately 15.2526). The peak signal-to-noise ratio on the M3FD dataset is 16.5044, which is 0.7480 higher than the best benchmark method YDTR (peak signal-to-noise ratio of approximately 15.7564). The peak signal-to-noise ratio on the TNO dataset is 17.3956, which is 0.7934 higher than the best benchmark method YDTR (peak signal-to-noise ratio: approximately 16.6022), and the overall performance on all other indicators is among the top in all comparison models. This method has broad application prospects in fields such as drone data fusion.

In this study, the Pb/U fractionation between zircon and uraninite during femtosecond Laser Ablation Inductively Coupled Plasma Mass Spectrometry （fs-LA-ICP-MS） analysis was studied in detail. The results show significant Pb/U fractionation between zircon and uraninite during fs-LA-ICP-MS analysis that when calibrated against the zircon standard M257, the obtained U-Pb age of the Chinese national uraninite standard GBW04420 is 17% older than the recommended value. Thus, the accurate in-situ U-Pb dating of uraninite by LA-ICP-MS requires matrix-matched external standards for calibration. Uraninite in thin sections of two U-mineralized leucogranite from the Gaudeanmus in Namibia was analyzed by a fs-LA-ICP-MS equipped with a Signal Smooth Device （SSD）, using laser spot and frequency of 10 μm and 1 Hz, respectively. When calibrated using GBW04420 as the external standard, two samples give weighted mean 2066pb/238U ages of 504±3 Ma （2σ, n=21） and 503±3 Ma （2σ, n=22）, and only one of two samples yields a concordia U-Pb age of 507±1 Ma （2or, n=21）. These results are consistent with ID-TIMS U-Pb ages of 509±1 and 508±12 Ma and are also indistinguishable from zircon U-Pb upper intercept ages of 506±33 Ma （2σ, n=29） and 501±51 Ma （2σ, n=29）. The present study shows that in-situ U-Pb dating of uraninite can deliver more reliable formation ages of the deposit than dating coeval high-U zircon because the latter commonly suffer significant Pb loss after formation. Our results confirm that GBW04420 is an ideal matrix matching standard for in-situ U-Pb dating of uraninite.

Images captured in a low-light environment are strongly influenced by noise and low contrast, which is detrimental to tasks such as image recognition and object detection. Retinex-based approaches have been continuously explored for low-light enhancement. Nevertheless, Retinex decomposition is a highly ill-posed problem. The estimation of the decomposed components should be combined with proper constraints. Meanwhile, the noise mixed in the low-light image causes unpleasant visual effects. To address these problems, we propose a Constraint Low-Rank Approximation Retinex model (CLAR). In this model, two exponential relative total variation constraints were imposed to ensure that the illumination is piece-wise smooth and that the reflectance component is piece-wise continuous. In addition, the low-rank prior was introduced to suppress the noise in the reflectance component. With a tailored separated alternating direction method of multipliers (ADMM) algorithm, the illumination and reflectance components were updated accurately. Experimental results on several public datasets verify the effectiveness of the proposed model subjectively and objectively.

Actinidia arguta is the most basal species in a phylogenetically and economically important genus in the family Actinidiaceae. To better understand the molecular basis of the Actinidia arguta chloroplast (cp), we sequenced the complete cp genome from A. arguta using Illumina and PacBio RS II sequencing technologies. The cp genome from A. arguta was 157,611 bp in length and composed of a pair of 24,232 bp inverted repeats (IRs) separated by a 20,463 bp small single copy region (SSC) and an 88,684 bp large single copy region (LSC). Overall, the cp genome contained 113 unique genes. The cp genomes from A. arguta and three other Actinidia species from GenBank were subjected to a comparative analysis. Indel mutation events and high frequencies of base substitution were identified, and the accD and ycf2 genes showed a high degree of variation within Actinidia. Forty-seven simple sequence repeats (SSRs) and 155 repetitive structures were identified, further demonstrating the rapid evolution in Actinidia. The cp genome analysis and the identification of variable loci provide vital information for understanding the evolution and function of the chloroplast and for characterizing Actinidia population genetics.

Atherosclerosis is featured as chronic low-grade inflammation in the arteries, which leads to the formation of plaques rich in lipids. M2 macrophage-derived extracellular vesicles (M2EV) have significant potential for anti-atherosclerotic therapy. However, their therapeutic effectiveness has been hindered by their limited targeting capability in vivo. The objective of this study was to create the P-M2EV (platelet membrane-modified M2EV) using the membrane fusion technique in order to imitate the interaction between platelets and macrophages. P-M2EV exhibited excellent physicochemical properties, and microRNA (miRNA)-sequencing revealed that the extrusion process had no detrimental effects on miRNAs carried by the nanocarriers. Remarkably, miR-99a-5p was identified as the miRNA with the highest expression level, which targeted the mRNA of Homeobox A1 (HOXA1) and effectively suppressed the formation of foam cells in vitro. In an atherosclerotic low-density lipoprotein receptor-deficient (Ldlr−/−) mouse model, the intravenous injection of P-M2EV showed enhanced targeting and greater infiltration into atherosclerotic plaques compared to regular extracellular vesicles. Crucially, P-M2EV successfully suppressed the progression of atherosclerosis without causing systemic toxicity. The findings demonstrated a biomimetic platelet-mimic system that holds great promise for the treatment of atherosclerosis in clinical settings. [Display omitted] •Platelet-mimic M2 macrophage-derived extracellular vesicles (P-M2EV) treatment of atherosclerosis.•miR-99a-5p targets HOXA1 and inhibits foam cell formation in vitro.•P-M2EV treatment shows better plaque targeting and deeper penetration in vivo.•P-M2EV alleviates atherosclerosis development without causing systemic toxicity.

Efficient and adaptive mission planning for Earth Observation Satellites (EOSs) remains a challenging task due to the growing complexity of user demands, task constraints, and limited satellite resources. Traditional heuristic and metaheuristic approaches often struggle with scalability and adaptability in dynamic environments. To overcome these limitations, we introduce AEM-D3QN, a novel intelligent task scheduling framework that integrates Graph Neural Networks (GNNs) with an Adaptive Exploration Mechanism-enabled Double Dueling Deep Q-Network (D3QN). This framework constructs a Directed Acyclic Graph (DAG) atlas to represent task dependencies and constraints, leveraging GNNs to extract spatial–temporal task features. These features are then encoded into a reinforcement learning model that dynamically optimizes scheduling policies under multiple resource constraints. The adaptive exploration mechanism improves learning efficiency by balancing exploration and exploitation based on task urgency and satellite status. Extensive experiments conducted under both periodic and emergency planning scenarios demonstrate that AEM-D3QN outperforms state-of-the-art algorithms in scheduling efficiency, response time, and task completion rate. The proposed framework offers a scalable and robust solution for real-time satellite mission planning in complex and dynamic operational environments.