Scientific Reports最新文献

The increasing requirement for lightweight and high-performance materials in the automotive industry has prompted significant research efforts focused on hybrid fiber-reinforced polymer composites. This study looked at making and carefully testing epoxy-based composites that were strengthened with Kevlar, basalt, and S-glass fibers, using 10% carbon powder as an added material. The study created single-fiber, dual-fiber hybrid, and tri-fiber hybrid laminates using the hand lay-up method, which allowed for controlled stacking sequences. Mechanical characterization was conducted following ASTM standards, encompassing tensile, flexural, impact, and hardness evaluations. The results show that using a mix of different fibers significantly improves mechanical properties compared to using just one type of fiber. Specifically, the basalt-Kevlar-S-glass tri-hybrid composite demonstrated a peak tensile strength of 354.37 N/mm², an outstanding flexural strength of 1350 N/mm², a maximum energy absorption capacity of 7.2 J, and the highest hardness level recorded at 115 RHN. These metrics reflect an exceptional ability to bear loads, resist bending, tolerate impacts, and maintain surface durability. The better performance is mainly due to how well the materials work together, the strong connections between the fibers and the matrix, and the added strength from the carbon filler. To support the experimental results, a TOPSIS analysis was done using Python, treating all criteria equally. The tri-hybrid composite demonstrated the highest closeness coefficient (CC = 1.000), thereby affirming its preeminence. The hybrid composites formulated exhibit significant promise for applications in lightweight automotive structures, specifically in the context of roof panels and load-bearing elements.

Streptomyces species are valuable allies in sustainable agriculture due to their ability to produce a diverse range of bioactive metabolites. This current study aimed to investigate the antioxidant, plant growth-promoting, and biocontrol potential of Streptomyces sp. SP5 against Fusarium wilt in Capsicum annuum. SP5 acetone precipitates and Et₂O extract exhibited strong dose-dependent antioxidant activity in multiple radical scavenging assays. In vitro seed bioassays with Vigna radiata revealed that SP5-derived indole-3-acetic acid markedly enhanced germination and early seedling growth, which was further supported by improved vegetative growth in pot experiments with Solanum lycopersicum. Furthermore, SP5 displayed remarkable biocontrol efficacy against Fusarium solani in Capsicum annuum. Under in vivo conditions, SP5 significantly reducing wilt incidence while simultaneously improving plant vigor and agronomic traits. SP5 treatments also enhanced photosynthetic pigment levels and stimulated the accumulation of phenolic and flavonoid compounds, indicating activation of plant defense responses under both stressed and non-stressed conditions. Overall, Streptomyces sp. SP5 functions as a multifunctional strain with combined antioxidant, growth-promoting, and biocontrol properties, highlighting its potential as an eco-friendly strategy for improving crop productivity and disease management.

Black rhinoceros are critically endangered due to poaching in the wild (in situ). Globally, fewer than 200 animals are maintained as an ex situ insurance population. Unfortunately, the ex situ population faces major sustainability challenges from disease syndromes characterized by high inflammatory burdens and diverse manifestations of immunometabolic dysfunction, not known to be present among their wild counterparts. Overlapping ex situ disease phenotypes limit diagnostic specificity and highlight the need to define underlying disease mechanisms. In the present study, using a cohort of presumed clinically healthy and inflammatory black rhinoceros, we generated the first immunoproteomic profile of any endangered mammal species and identified 1,311 immune cell proteins. However, no significant differences were detected among clinical phenotypes. Therefore, we applied unsupervised machine learning approaches to detect molecular features suggestive of healthy versus inflammatory phenotypes. Forty-three proteins associated with inflammatory pathways were differentially expressed in a cohort of samples derived from both presumed healthy and inflammatory phenotypes. Results suggest subclinical disease may be relatively widespread ex situ, and that animals experience temporal fluctuations in inflammatory state over time. Findings implicate neutrophil degranulation and dysregulation of the oral-gut-liver axis as drivers of disease syndromes of ex situ black rhinoceros. The forty-three proteins associated with inflammatory pathways represent candidate inflammatory biomarkers to be assessed for clinical applications in future validation studies. Upon validation, these candidate biomarkers may guide management practices to strengthen long-term population sustainability.

Multimodal industrial documents-such as operation manuals, circuit diagrams, and parameter tables-contain domain knowledge distributed across text, images, and document layout. However, most existing retrieval-augmented generation (RAG) frameworks rely on static retrieval and fusion policies with fixed modality weights and uniform retrieval depth, making them less adaptable to diverse query intents and dynamic cross-modal dependencies. As a result, they often retrieve incomplete evidence and yield suboptimal reasoning in complex long-document scenarios. To address these challenges, we propose MARL-RAGDoc, a hierarchical multi-agent reinforcement learning framework for multimodal retrieval-augmented reasoning. A high-level coordinator agent dynamically allocates modality weights and retrieval depth based on query characteristics, while specialized text, image, and table agents perform fine-grained evidence selection within their respective candidate pools. A collaborative reasoning module integrates the retrieved evidence and provides hierarchical reward signals to continuously optimize retrieval policies. Experimental results on multiple multimodal document benchmarks demonstrate that MARL-RAGDoc consistently outperforms baselines in both retrieval accuracy and reasoning performance, while remaining computationally efficient. Our code and dataset are publicly available at https://github.com/Yihong-Q/MARL-RAGDoc.

The dissemination route of brain metastases dictates their spatiotemporal distribution, but whether it alters the ultrastructural state of the blood-tumor barrier remains unresolved. Here, we compared a modified hematogenous dissemination model that minimizes extracranial signal confounds with a direct intracranial inoculation model. The hematogenous model produced multifocal brain lesions, whereas the intracranial model formed unifocal masses. Longitudinal bioluminescence imaging revealed significantly different growth rates between models, yet no statistically significant difference in overall survival was detected under the current cohort sizes and humane endpoints. Critically, exploratory transmission electron microscopy at the tumor-brain interface revealed a conserved pathological phenotype of the blood-tumor barrier in established lesions, irrespective of the seeding route. This pattern was characterized by endothelial cell swelling, a discontinuous basement membrane, and retraction of astrocytic end-feet. These findings suggest that while the seeding route determines the macroscopic pattern of disease, the established brain microenvironment imposes a stereotyped mode of neurovascular unit failure. This work provides a methodologically refined platform for studying brain metastasis and presents direct ultrastructural evidence consistent with a conserved blood-tumor barrier pathology, outlining a testable conceptual framework. These hypothesis-generating ultrastructural observations, derived from representative specimens, warrant quantitative validation.

Heart failure (HF) is a common disease resulting in high morbidity, mortality, and healthcare costs. An important cause of HF is mitral valve regurgitation (MR), which induces left ventricular remodeling and volume overload. For HF research, a reproducible and reliable large animal model is crucial. Several MR models have been developed, but they often show high variability in MR severity and MR jet characteristics, as well as an underlying ischemic cardiomyopathy, which may increase the risk of complications during follow-up. We present a straightforward and uniform porcine model of primary MR-induced HF. A custom-made retractor was used to induce severe and uniform MR by chordal rupture. After four weeks, severe MR led to significant left ventricular remodeling compared to the sham group, with a significant increase in left ventricular end-diastolic (+34.5 ± 6.8 ml vs. +8.4 ± 5.3 ml, p = 0.023) and end-systolic volume (+29.9 ± 4.0 ml vs. +4.2 ± 2.9 ml, p = 0.001), a decrease in left ventricular ejection fraction (-11.9 ± 1.9% vs. -0.7 ± 0.9%, p < 0.001) and fractional shortening (-12.2 ± 1.3% vs. -2.2 ± 0.8%, p < 0.001), and a higher amount of left ventricular fibrosis (12.6 ± 1.0% vs. 6.4 ± 0.9%, p = 0.001). This porcine model allows a straightforward and reproducible induction of primary MR-induced HF, with a high success rate. It could be valuable in basic research to study the underlying pathophysiology and in translational research to develop novel diagnostics and therapeutics targeting volume-overload induced HF and/or primary MR.

Expediting the construction of the new energy systems is crucial to achieving an energy transition, decreasing carbon dioxide emissions, and alleviating global warming. Utilizing Chinese province panel data from 2000 to 2022, we examined the causal effect of diversity in financial ecosystems on the new energy systems and utilized instrumental variable estimates to mitigate endogeneity. We constructed a new energy systems indicator framework, employed the entropy approach to assign weights to each indicator objectively, and quantitatively assessed the level and attributes of the new energy systems. The findings indicate that diversity in financial ecosystems plays a crucial role in developing new energy systems. Diversity in financial ecosystems impacts the development of new energy systems via the consequences of technology innovation and digital effects. These effects are more concentrated in areas without external power inputs, with a long transportation history, and characterized by low bird biodiversity. The study's findings offer a viable Chinese approach for global energy transition and successful climate change mitigation.