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Background Roseobacteraceae , often referred to as the marine roseobacter clade (MRC), are pivotal constituents of bacterial communities in coastal and pelagic marine environments. During the past two decades, 75 roseophages that infect various Roseobacteraceae lineages have been isolated. The N4-like roseophage clade, which encompasses 15 members, represents the largest clade among these roseophages. N4-like phages form a monophyletic group, classified as family Schitoviridae . And all N4-like roseophages form a unique clade within Schitoviridae and has been classified as the Rhodovirinae subfamily. Results In this study, we isolated a novel roseophage, vB_DshP-R7L, that infects Dinoroseobacter shibae DFL12 from Xiamen Bay in the East China Sea. Conserved genes of Schitoviridae have been identified in the genome of vB_DshP-R7L, and following phylogenetic analysis suggests that the newly isolated phage is a member of the Rhodovirinae subfamily and represents the sole member of a novel genus, Gonggongvirus . The genome of vB_DshP-R7L harbors six auxiliary metabolic genes (AMGs), most of which potentially enhance DNA de novo synthesis. Additionally, a gene encoding ribosomal protein was identified. Comparative genomic analysis of AMG content among Rhodovirinae indicates a distinct evolutionary history characterized by independent ancient horizontal gene transfer events. Read-mapping analysis reveals the prevalence of vB_DshP-R7L and other Rhodovirinae roseophages in estuarine waters. Conclusions Our work illustrates the genomic features of a novel roseophage clade among the subfamily Rhodovirinae. The AMG content of vB_DshP-R7L is under severe purification selection, which reveals their possible ecological importance. We also demonstrated that vB_DshP-R7L and other Rhodovirinae roseophages are only detected in estuaries. Our isolation and characterization of this novel phage expands the understanding of the phylogeny, gene transfer history, and biogeography of Rhodovirinae infecting marine Roseobacteraceae.

Soft nano electronic materials based on conductive hydrogels have attracted considerable attention due to their exceptional properties. Particle deposition and poor interface compatibility often diminish the mechanical strength and electron transport capabilities of the conductive hydrogel. Mechanical damage can severely impact the performance of the conductive hydrogel and can even damage electronic devices based on the conductive hydrogel. In the current study, a transparent nano-silica hydrogel is prepared by employing an extremely easy-to-operate method. This approach can preclude the deposition of particles via strong mechanical force. In addition, controlling the concentration of the reaction interface makes the hydrogel grow along the mechanical force in the direction with a special directional hole structure formed. The hydrogel is transparent, showing excellent self-healing properties—it can self-heal within 15 seconds. Remarkably, the hydrogel after self-healing maintains its performance. Moreover, it has excellent mechanical properties and can be stretched in length. Up to 1,200% of the original length, the tensile strength of the gel spline can reach 7 MPa. The viscosity of the hydrogel can reach 1.67 × 10 8 (MPs). In addition, a large amount of Na + in this hydrogel endow it a conductivity of 389 ε/cm. The conductivity of this hydrogel is adjustable result from the special pore structure. Lastly, the difference between the horizontal and vertical conductivity of the same sample can reach 3–4 times, thus this hydrogel can be used in the field of nano conductive materials.

Carbon fibers (CFs) have been the most popular material for decades and compound into various materials because of their excellent performance. Herein, a novel one-step hot pressing molding is proposed to prepare polyacrylonitrile (PAN) CFs, eliminating the time-consuming and energy-consuming thermal stabilization stage. The fibers are tiled and pressed tightly between the two plates. The unit is then carbonized in a tubular furnace. Hot pressing enforced the fiber structure to be cyclized and reduces the damage of fibers by mitigating the escape of heteroatoms gas. The thermoplasticity of PAN fibers is innovatively utilized in the preparation of carbon fibers by hot pressing, which is able to improve density and repair the cracks. The density and tensile strength of fibers at 900 °C have reached to 1.70 g cm−3 and 1.1GPa. The CFs obtained by hot pressing molding have not only a smooth surface morphology, but also a high degree of microstructure cyclization. Hot pressing molding can not only realize the function of thermal stability stage, but also simplify the process, save energy and time, and reduce the cost.

Accurate segmentation and anatomical classification of vertebrae in spinal CT scans are crucial for clinical diagnosis, surgical planning, and disease monitoring. However, the task is complicated by anatomical variability, degenerative changes, and the presence of rare vertebral anomalies. In this study, we propose a hybrid framework that combines a high-resolution WNet segmentation backbone with a Vision Transformer (ViT)-based classification module to perform vertebral identification and anomaly detection. Our model incorporates an attention-based anatomical variation module and leverages patient-specific metadata (age, sex, vertebral distribution) to improve the accuracy and personalization of vertebrae typing. Extensive experiments on the VerSe 2019 and 2020 datasets demonstrate that our approach outperforms state-of-the-art baselines such as nnUNet and SwinUNet, especially in detecting transitional vertebrae (e.g., T13, L6) and modeling morphological diversity. The system maintains high robustness under slice skipping, noise perturbation, and scanner variations, while offering interpretability through attention heatmaps and case-specific alerts. Our findings suggest that integrating anatomical priors and demographic context into transformer-based pipelines is a promising direction for personalized, intelligent spinal image analysis.

Fructus Aurantii (FA) is a valuable medicinal material used in traditional China medicine. Predicting the suitable distribution areas of FA and identifying its potential distribution patterns driven by various environmental factors are crucial for the selection of planting sites and maintenance of medicinal quality. Here, the maximum entropy model was used to predict the potential distribution of FA in Jiangxi Province, China under current and future climate conditions. A total of 105 geographical distribution data of FA were collected through field investigation and 32 environmental variables were obtained from public databases. The maximum entropy model showed high prediction accuracy when 16 environmental variables were selected (AUC = 0.932). The habitat suitability of FA was prominently affected by climate, which surpassed topography and soil factors. Maximum temperature of the warmest month, annual temperature range, precipitation of the wettest month, precipitation coefficient of variation, elevation, aspect, and soil organic carbon were the key factors shaping the geographic distribution of FA. Among them, maximum temperature of the warmest month (16.9%), followed by annual temperature range (16.1%), made the greatest contribution to model predictions. In the current climate background, the total potential suitable area for FA covered 6.30 × 10 4 km 2 of garden land. Under future climate warming scenarios (shared socioeconomic pathways 245, 585), the potential suitable area was predicted to move southward and expand twice in 2040–2080, with notable increase in moderately and poorly suitable areas. Low hilly areas at higher elevations with moist cool conditions and gentle undulations would become more suitable for future introduction and planting of FA. Regionalized strategies for different suitable planting areas were proposed taking into account future climate change. All data are available in Mendeley Data (DOI: 10.17632/s9wsnn2xcn.1). Code is available at https://github.com/mrmaxent/Maxent .

Green and renewable cellulosic materials are considered promising candidates for replacing conventional petroleum-based plastics. Herein, alkaline extrusion pretreatment (AEP) assisted with acetylation was applied to prepare a thermoplastic material with a high degree of acetylation (52.2%) and directly from lignocellulose biomass. AEP, utilized as an innovative and industrial process, can efficiently swell lignocellulose fibres, destroy their structure, and promote the accessibility of lignocellulose. To explore the mechanism of the AEP process on the transformation of lignocellulose polymorphism, the compositions and crystalline structure of all samples were characterized and analysed. The obtained acetylated lignocellulose possesses great thermal and thermoplastic properties (low glass transition temperature of 135 °C). In general, the proposed industrially-viable approach in this work is conducive to developing a highly acetylated lignocellulose material via high-value utilization of the whole lignocellulose composition. Graphical abstract

Computer vision-based displacement measurement techniques are increasingly used for structural health monitoring. However, the vision sensors employed are easily affected by optical turbulence when capturing images of the structure, resulting in displacement measurement errors that significantly reduce the accuracy required in engineering applications. Hence, this paper develops a multi-measurement point method to address this problem by mitigating optical-turbulence errors with spatial randomness. Then, the effectiveness of the proposed method in mitigating optical-turbulence errors is verified by static target experiments, in which the RMSE correction rate can reach up to 82%. Meanwhile, the effects of target size and the number of measurement points on the proposed method are evaluated, and the optimal target design criteria are proposed to improve our method’s performance in mitigating optical-turbulence errors under different measurement conditions. Additionally, extensive dynamic target experiments reveal that the proposed method achieves an RMSE correction rate of 69% after mitigating the optical-turbulence error. The experimental results demonstrate that the proposed method improves the visual displacement measurement accuracy and retains the detailed information of the displacement measurement results.

s White organic light-emitting diodes (WOLEDs) show very promising as next-generation light-sources, but achieving high power efficiency (PE) and long operational lifetime remains challenging because of the lack of stable blue emitters that can harvest all triplet (T 1 ) excitons for light emission. Herein, we propose integrating stable azure multi-resonance thermally activated delayed fluorescent (MR-TADF) emitters into tri-color hybrid WOLEDs to tackle these issues. By meticulously selecting MR-TADF emitters and precisely tuning the exciton recombination zone, the optimized tri-color devices based on BCzBN-3B achieve color-stable white light emission with maximum external quantum efficiency (EQE max ) and maximum PE (PE max ) of 34.4% and 101.8 lm W −1 , respectively. Furthermore, the LT 90 , defined as the time for the luminance to drop to 90% of its initial value at 1000 cd m −2 , reaches 761 h. In addition, a hybrid WOLED with deep blue emitter developed using our strategy achieves a high color rendering index of 88 and an EQE max of 30.6%, further demonstrating the versatility and effectiveness of our approach. The record-breaking efficiency and ultra-long lifetime underscore the success of hybrid white-light devices by incorporating robust blue MR-TADF emitters. These advancements open new avenues for commercialization of hybrid WOLEDs, presenting promising solutions for energy-efficient lighting and display technologies. A tri-color emitting layer design incorporating robust blue multi-resonance emitters creates high-performance white light-emitting diodes with EQE max of 34.4%, PE max of 101.8 lm W − 1 , and LT 90 value of 761 h.

Curcumin has good anti-cancer and antioxidant properties. However, the poor water solubility and low bioavailability limit its application in food products. This study constructed a nanostructured lipid carrier (Cur-CLA-NLC) encapsulating curcumin using conjugated linoleic acid (CLA) as the liquid lipid and stearic acid as the solid lipid. Cur-CLA-NLC exhibits significantly enhanced bioaccessibility, antioxidant activity, and cytocompatibility. CLA, as a liquid lipid in Cur-CLA-NLC, has a dual role as a structural stabilizer and bioactive agent, and synergistically enhances antioxidant activity with curcumin. In vitro simulated digestion studies showed that the bioaccessibility of curcumin in Cur-CLA-NLC (85.7%) was much higher than that in the pure curcumin (11.7%) and curcumin lipid mixtures (9.3%). In addition, the Cur-CLA-NLC system showed anti-lipid peroxidation ability and good biocompatibility. Therefore, CLA-NLC can serve as a potential delivery system for enhancing health benefits via functional foods.

The emergence and rapid spread of methicillin‐resistant Staphylococcus aureus (MRSA) raise a critical need for alternative therapeutic options. New antibacterial drugs and targets are required to combat MRSA‐associated infections. Based on this study, celastrol, a natural product from the roots of Tripterygium wilfordii Hook. f., effectively combats MRSA in vitro and in vivo. Multi‐omics analysis suggests that the molecular mechanism of action of celastrol may be related to Δ1‐pyrroline‐5‐carboxylate dehydrogenase (P5CDH). By comparing the properties of wild‐type and rocA‐deficient MRSA strains, it is demonstrated that P5CDH, the second enzyme of the proline catabolism pathway, is a tentative new target for antibacterial agents. Using molecular docking, bio‐layer interferometry, and enzyme activity assays, it is confirmed that celastrol can affect the function of P5CDH. Furthermore, it is found through site‐directed protein mutagenesis that the Lys205 and Glu208 residues are key for celastrol binding to P5CDH. Finally, mechanistic studies show that celastrol induces oxidative stress and inhibits DNA synthesis by binding to P5CDH. The findings of this study indicate that celastrol is a promising lead compound and validate P5CDH as a potential target for the development of novel drugs against MRSA. Schematic diagram summarizing the antibacterial mechanisms of celastrol against MRSA. Celastrol activates multiple pathways including inhibiting DNA and protein biosynthesis, generating ROS and inducing cell death by competitively binding to P5CDH.