Does it stable? Intracranial aneurysm wall enhancement might be the warning signals: a meta-analysis of observational studies.

Magnetic resonance vessel wall imaging (MR-VWI) is an emerging imaging technology used to assess the progressive risk of unruptured intracranial aneurysms (UIAs). Unlike the standard evaluation model, MR-VWI is still debatable. This study aims to further define the potential relationship between aneurysm wall enhancement (AWE) and aneurysm stability. Using "intracranial aneurysm", "magnetic resonance", and "enhancement" as keywords, relevant studies were systematically searched in PubMed, Embase, and Cochrane, and the qualified studies were enrolled for further analysis. There were 13 case-control studies, 4 cohort studies, and 2,678 cases of intracranial aneurysms included in the meta-analysis. It was shown that AWE was correlated with intracranial aneurysm rupture (OR = 35.90, 95% CI: 15.58 to 82.75, p < 0.001), growth (OR = 6.69, 95% CI: 2.69 to 16.63, p < 0.001), and presence of symptoms (OR = 14.46, 95% CI: 9.07 to 23.05, p < 0.001). This finding had a high diagnostic value, but the correlation was probably not independent of aneurysm size. The pooled relative risks of the follow-up studies revealed that the risk of UIA progression was approximately 3.33 times higher with AWE than without AWE (RR = 3.33, 95% CI: 2.33 to 4.78, p < 0.001). In addition, the pooled results demonstrated that quantitative indices of VWI enhancement were equally linked with aneurysm stability (OR = 19.61, 95% CI: 10.63 to 36.17, p < 0.001). AWE is an effective imaging method to assess the stability of UIAs, and it can be a marker for the prophylactic treatment of small unruptured intracranial aneurysms in the future, which remains to be validated by prospective studies with large samples.

Investor characteristics, intention toward socially responsible investment (SRI), and SRI behavior in Chinese stock market: The moderating role of risk propensity.

In recent years, Socially Responsible Investment (SRI), which integrates financial returns with social impact, has gained prominence. Commonly referred to as ethical or green investing, this study employs the Theory of Planned Behavior (TPB) to analyze factors that influence SRI behaviors. The TPB model suggests that behavior is primarily influenced by attitudes, subjective norms, perceived behavioral control (PBC), and intention. The study uniquely adapts the TPB model by incorporating financial literacy as a critical factor, a hypothesis substantiated through primary data from Chinese investors. Furthermore, the research highlights risk propensity as a moderating variable, significantly affecting these dynamics and offering essential insights into SRI practices. By utilizing Structural Equation Modeling (SEM) in conjunction with TPB, the study investigates the behavioral patterns of investors in Chinese stock market with a specific focus on the impacts of financial literacy, the moderating role of risk propensity, and the mediating effects of investment intentions on SRI behaviors. The findings reveal that PBC plays the most crucial role in shaping investors' intentions and behaviors toward SRI. Additionally, the results recommend that policymakers and SRI providers consider the social influences on investors' decisions and acknowledge the significant impact of investors' perceived control in forming their SRI intentions and actions.

Identification of Coupled Landau and Anomalous Resonances in Space Plasmas.

Wave-particle resonance, a ubiquitous process in the plasma universe, occurs when resonant particles observe a constant wave phase to enable sustained energy transfer. Here, we present spacecraft observations of simultaneous Landau and anomalous resonances between oblique whistler waves and the same group of protons, which are evidenced, respectively, by phase-space rings in parallel-velocity spectra and phase-bunched distributions in gyrophase spectra. Our results indicate the coupling between Landau and anomalous resonances via the overlapping of the resonance islands.

Servant leadership and project success: the mediating roles of team learning orientation and team agility.

Drawing from social learning theory, this study aims to explore the mediating effects of team learning orientation and team agility on the relationship between servant leadership and project success in the context of construction projects. Based on data collected from 306 construction project members in China, the findings reveal that servant leadership exerts a positive influence on project success. Additionally, servant leadership significantly enhances both team learning orientation and team agility, which in turn contribute to project success. Furthermore, the results demonstrate the serial and parallel mediating roles of team learning orientation and team agility between servant leadership and project success. Theoretical and practical implications were also provided based on the findings.

Nitrate transporters and mechanisms of nitrate signal transduction in Arabidopsis and rice.

Nitrate (NO3 -) is a significant inorganic nitrogen source in soil, playing a crucial role in influencing crop productivity. As sessile organisms, plants have evolved complex mechanisms for nitrate uptake and response to varying soil levels. Recent advancements have enhanced our understanding of nitrate uptake and signaling pathways. This mini-review offers a comparative analysis of nitrate uptake mechanisms in Arabidopsis and rice. It also examines nitrate signal transduction, highlighting the roles of AtNRT1.1 and AtNLP7 as nitrate receptors and elucidating the OsNRT1.1B-OsSPX4-OsNLP3 cascade. Additionally, it investigates nuclear transcriptional networks that regulate nitrate-responsive genes, controlled by various transcription factors (TFs) crucial for plant development. By integrating these findings, we highlight mechanisms that may help to enhance crop nitrogen utilization.

Wireless Magnetic Robot for Precise Hierarchical Control of Tissue Deformation.

Mechanotherapy has emerged as a promising treatment for tissue injury. However, existing robots for mechanotherapy are often designed on intuition, lack remote and wireless control, and have limited motion modes. Herein, through topology optimization and hybrid fabrication, wireless magneto-active soft robots are created that can achieve various modes of programmatic deformations under remote magnetic actuation and apply mechanical forces to tissues in a precise and predictable manner. These soft robots can quickly and wirelessly deform under magnetic actuation and are able to deliver compressing, stretching, shearing, and multimodal forces to the surrounding tissues. The design framework considers the hierarchical tissue-robot interaction and, therefore, can design customized soft robots for different types of tissues with varied mechanical properties. It is shown that these customized robots with different programmable motions can induce precise deformations of porcine muscle, liver, and heart tissues with excellent durability. The soft robots, the underlying design principles, and the fabrication approach provide a new avenue for developing next-generation mechanotherapy.

Electroacupuncture remodels gut microbiota and metabolites in mice with perioperative neurocognitive impairment.

Gut microbiota and metabolites are considered key factors in the pathogenesis of perioperative neurocognitive disorders (PND), and the brain-gut axis may be a promising target for PND treatment. Electroacupuncture has been shown to improve a wide range of neurological disorders and to restore function to the gastrointestinal tract. Thus, we hypothesized whether electroacupuncture could remodel gut microbiota and neuroinflammation induced by anesthesia/surgery. First, we observed electroacupuncture at acupoints GV20, LI4 and PC6 significantly improved memory in behavioral tests. Next, we found electroacupuncture decreased the levels of inflammatory factors (NSE, S-100ß, IL-6, etc.) in the hippocampus, indicating that nerve inflammation was blocked by electroacupuncture. Furthermore, via 16S rRNA sequence analysis and LC-MS analysis, the gut microbiota and its metabolites were appropriately restored after electroacupuncture treatment. Additionally, we further confirmed the restorative effect of electroacupuncture on PND by fecal transplantation. In conclusion, the role of electroacupuncture in improving cognitive function and protecting neurons may be related to the modulation of gut microbiota and their metabolite dysregulation, thereby inhibiting neuroinflammation in PND mice.

Analytical realization of complex thermal meta-devices.

Fourier's law dictates that heat flows from warm to cold. Nevertheless, devices can be tailored to cloak obstacles or even reverse the heat flow. Mathematical transformation yields closed-form equations for graded, highly anisotropic thermal metamaterial distributions needed for obtaining such functionalities. For simple geometries, devices can be realized by regular conductor distributions; however, for complex geometries, physical realizations have so far been challenging, and sub-optimal solutions have been obtained by expensive numerical approaches. Here we suggest a straightforward and highly efficient analytical de-homogenization approach that uses optimal multi-rank laminates to provide closed-form solutions for any imaginable thermal manipulation device. We create thermal cloaks, rotators, and concentrators in complex domains with close-to-optimal performance and esthetic elegance. The devices are fabricated using metal 3D printing, and their omnidirectional thermal functionalities are investigated numerically and validated experimentally. The analytical approach enables next-generation free-form thermal meta-devices with efficient synthesis, near-optimal performance, and concise patterns.

Grazing decreases net ecosystem carbon exchange by decreasing shrub and semi-shrub biomass in a desert steppe.

Livestock grazing can strongly determine how grasslands function and their role in the carbon cycle. However, how ecosystem carbon exchange responds to grazing and the underlying mechanisms remain unclear. We measured ecosystem carbon fluxes to explore the changes in carbon exchange and their driving mechanisms under different grazing intensities (CK, control; HG, heavy grazing; LG, light grazing; MG, moderate grazing) based on a 16-year long-term grazing experimental platform in a desert steppe. We found that grazing intensity influenced aboveground biomass during the peak growing season, primarily by decreasing shrubs and semi-shrubs and perennial forbs. Furthermore, grazing decreased net ecosystem carbon exchange by decreasing aboveground biomass, especially the functional group of shrubs and semi-shrubs. At the same time, we found that belowground biomass and soil ammonium nitrogen were the driving factors of soil respiration in grazed systems. Our study indicates that shrubs and semi-shrubs are important factors in regulating ecosystem carbon exchange under grazing disturbance in the desert steppe, whereas belowground biomass and soil available nitrogen are important factors regulating soil respiration under grazing disturbance in the desert steppe; this results provide deeper insights for understanding how grazing moderates the relationships between soil nutrients, plant biomass, and ecosystem CO2 exchange, which provide a theoretical basis for further grazing management.

Modulate stress distribution with bio-inspired irregular architected materials towards optimal tissue support.

Natural materials typically exhibit irregular and non-periodic architectures, endowing them with compelling functionalities such as body protection, camouflage, and mechanical stress modulation. Among these functionalities, mechanical stress modulation is crucial for homeostasis regulation and tissue remodeling. Here, we uncover the relationship between stress modulation functionality and the irregularity of bio-inspired architected materials by a generative computational framework. This framework optimizes the spatial distribution of a limited set of basic building blocks and uses these blocks to assemble irregular materials with heterogeneous, disordered microstructures. Despite being irregular and non-periodic, the assembled materials display spatially varying properties that precisely modulate stress distribution towards target values in various control regions and load cases, echoing the robust stress modulation capability of natural materials. The performance of the generated irregular architected materials is experimentally validated with 3D printed physical samples - a good agreement with target stress distribution is observed. Owing to its capability to redirect loads while keeping a proper amount of stress to stimulate bone repair, we demonstrate the potential application of the stress-programmable architected materials as support in orthopedic femur restoration.

Self-healing, antioxidant, and antibacterial Bletilla striata polysaccharide-tannic acid dual dynamic crosslinked hydrogels for tissue adhesion and rapid hemostasis.

Biomaterials capable of achieving effective sealing and hemostasis at moist wounds are in high demand in the clinical management of acute hemorrhage. Bletilla striata polysaccharide (BSP), a natural polysaccharide renowned for its hemostatic properties, holds promising applications in biomedical fields. In this study, a dual-dynamic-bonds crosslinked hydrogel was synthesized via a facile one-pot method utilizing poly(vinyl alcohol) (PVA)-borax as a matrix system, followed by the incorporation of BSP and tannic acid (TA). Chemical borate ester bonds formed around borax, coupled with multiple physical hydrogen bonds between BSP and other components, enhanced the mechanical properties and rapid self-healing capabilities. The catechol moieties in TA endowed the hydrogel with excellent adhesive strength of 30.2 kPa on the surface of wet tissues and facilitated easy removal without residue. Benefiting from the synergistic effect of TA and the preservation of the intrinsic properties of BSP, the hydrogel exhibited outstanding biocompatibility, antibacterial, and antioxidant properties. Moreover, it effectively halted acute bleeding within 31.3 s, resulting in blood loss of 15.6 % of that of the untreated group. As a superior hemostatic adhesive, the hydrogel in this study is poised to offer a novel solution for addressing future acute hemorrhage, wound healing, and other biomedical applications.

Brain-Heart Axis and the Inflammatory Response: Connecting Stroke and Cardiac Dysfunction.

BACKGROUND: In recent years, the mechanistic interaction between the brain and heart has been explored in detail, which explains the effects of brain injuries on the heart and those of cardiac dysfunction on the brain. Brain injuries are the predominant cause of post-stroke deaths, and cardiac dysfunction is the second leading cause of mortality after stroke onset. SUMMARY: Several studies have reported the association between brain injuries and cardiac dysfunction. Therefore, it is necessary to study the influence on the heart post-stroke to understand the underlying mechanisms of stroke and cardiac dysfunction. This review focuses on the mechanisms and the effects of cardiac dysfunction after the onset of stroke (ischemic or hemorrhagic stroke). KEY MESSAGES: The role of the site of stroke and the underlying mechanisms of the brain-heart axis after stroke onset, including the hypothalamic-pituitary-adrenal axis, inflammatory and immune responses, brain-multi-organ axis, are discussed.

GRAS transcription factor PINNATE-LIKE PENTAFOLIATA2 controls compound leaf morphogenesis in Medicago truncatula.

The milestone of compound leaf development is the generation of separate leaflet primordia during the early stages, which involves two linked but distinct morphogenetic events: leaflet initiation and boundary establishment for leaflet separation. Although some progress in understanding the regulatory pathways for each event have been made, it is unclear how they are intrinsically coordinated. Here, we identify the PINNATE-LIKE PENTAFOLIATA2 (PINNA2) gene encoding a newly identified GRAS transcription factor in Medicago truncatula. PINNA2 transcripts are preferentially detected at organ boundaries. Its loss-of-function mutations convert trifoliate leaves into a pinnate pentafoliate pattern. PINNA2 directly binds to the promoter region of the LEAFY orthologue SINGLE LEAFLET1 (SGL1), which encodes a key positive regulator of leaflet initiation, and downregulates its expression. Further analysis revealed that PINNA2 synergizes with two other repressors of SGL1 expression, the BEL1-like homeodomain protein PINNA1 and the C2H2 zinc finger protein PALMATE-LIKE PENTAFOLIATA1 (PALM1), to precisely define the spatiotemporal expression of SGL1 in compound leaf primordia, thereby maintaining a proper pattern of leaflet initiation. Moreover, we showed that the enriched expression of PINNA2 at the leaflet-to-leaflet boundaries is positively regulated by the boundary-specific gene MtNAM, which is essential for leaflet boundary formation. Together, these results unveil a pivotal role of the boundary-expressed transcription factor PINNA2 in regulating leaflet initiation, providing molecular insights into the coordination of intricate developmental processes underlying compound leaf pattern formation.

Metabolic tagging of extracellular vesicles and development of enhanced extracellular vesicle based cancer vaccines.

As key mediators of cellular communication, extracellular vesicles (EVs) have been actively explored for diagnostic and therapeutic applications. However, effective methods to functionalize EVs and modulate the interaction between EVs and recipient cells are still lacking. Here we report a facile and universal metabolic tagging technology that can install unique chemical tags (e.g., azido groups) onto EVs. The surface chemical tags enable conjugation of molecules via efficient click chemistry, for the tracking and targeted modulation of EVs. In the context of tumor EV vaccines, we show that the conjugation of toll-like receptor 9 agonists onto EVs enables timely activation of dendritic cells and generation of superior antitumor CD8+ T cell response. These lead to 80% tumor-free survival against E.G7 lymphoma and 33% tumor-free survival against B16F10 melanoma. Our study yields a universal technology to generate chemically tagged EVs from parent cells, modulate EV-cell interactions, and develop potent EV vaccines.

Control of compound leaf patterning by MULTI-PINNATE LEAF1 (MPL1) in chickpea.

Plant lateral organs are often elaborated through repetitive formation of developmental units, which progress robustly in predetermined patterns along their axes. Leaflets in compound leaves provide an example of such units that are generated sequentially along the longitudinal axis, in species-specific patterns. In this context, we explored the molecular mechanisms underlying an acropetal mode of leaflet initiation in chickpea pinnate compound leaf patterning. By analyzing naturally occurring mutants multi-pinnate leaf1 (mpl1) that develop higher-ordered pinnate leaves with more than forty leaflets, we show that MPL1 encoding a C2H2-zinc finger protein sculpts a morphogenetic gradient along the proximodistal axis of the early leaf primordium, thereby conferring the acropetal leaflet formation. This is achieved by defining the spatiotemporal expression pattern of CaLEAFY, a key regulator of leaflet initiation, and also perhaps by modulating the auxin signaling pathway. Our work provides novel molecular insights into the sequential progression of leaflet formation.

Research on the Detection Method of Organic Matter in Tea Garden Soil Based on Image Information and Hyperspectral Data Fusion.

Soil organic matter is an important component that reflects soil fertility and promotes plant growth. The soil of typical Chinese tea plantations was used as the research object in this work, and by combining soil hyperspectral data and image texture characteristics, a quantitative prediction model of soil organic matter based on machine vision and hyperspectral imaging technology was built. Three methods, standard normalized variate (SNV), multisource scattering correction (MSC), and smoothing, were first used to preprocess the spectra. After that, random frog (RF), variable combination population analysis (VCPA), and variable combination population analysis and iterative retained information variable (VCPA-IRIV) algorithms were used to extract the characteristic bands. Finally, the quantitative prediction model of nonlinear support vector regression (SVR) and linear partial least squares regression (PLSR) for soil organic matter was established by combining nine color features and five texture features of hyperspectral images. The outcomes demonstrate that, in comparison to single spectral data, fusion data may greatly increase the performance of the prediction model, with MSC + VCPA-IRIV + SVR (R2C = 0.995, R2P = 0.986, RPD = 8.155) being the optimal approach combination. This work offers excellent justification for more investigation into nondestructive methods for determining the amount of organic matter in soil.

Algorithmic encoding of adaptive responses in temperature-sensing multimaterial architectures.

We envision programmable matters that can alter their physical properties in desirable manners based on user input or autonomous sensing. This vision motivates the pursuit of mechanical metamaterials that interact with the environment in a programmable fashion. However, this has not been systematically achieved for soft metamaterials because of the highly nonlinear deformation and underdevelopment of rational design strategies. Here, we use computational morphogenesis and multimaterial polymer 3D printing to systematically create soft metamaterials with arbitrarily programmable temperature-switchable nonlinear mechanical responses under large deformations. This is made possible by harnessing the distinct glass transition temperatures of different polymers, which, when optimally synthesized, produce local and giant stiffness changes in a controllable manner. Featuring complex geometries, the generated structures and metamaterials exhibit fundamentally different yet programmable nonlinear force-displacement relations and deformation patterns as temperature varies. The rational design and fabrication establish an objective-oriented synthesis of metamaterials with freely tunable thermally adaptive behaviors. This imbues structures and materials with environment-aware intelligence.

NIR Spectral Inversion of Soil Physicochemical Properties in Tea Plantations under Different Particle Size States.

Soil fertility is vital for the growth of tea plants. The physicochemical properties of soil play a key role in the evaluation of soil fertility. Thus, realizing the rapid and accurate detection of soil physicochemical properties is of great significance for promoting the development of precision agriculture in tea plantations. In recent years, spectral data have become an important tool for the non-destructive testing of soil physicochemical properties. In this study, a support vector regression (SVR) model was constructed to model the hydrolyzed nitrogen, available potassium, and effective phosphorus in tea plantation soils of different grain sizes. Then, the successful projections algorithm (SPA) and least-angle regression (LAR) and bootstrapping soft shrinkage (BOSS) variable importance screening methods were used to optimize the variables in the soil physicochemical properties. The findings demonstrated that soil particle sizes of 0.25-0.5 mm produced the best predictions for all three physicochemical properties. After further using the dimensionality reduction approach, the LAR algorithm (R2C = 0.979, R2P = 0.976, RPD = 6.613) performed optimally in the prediction model for hydrolytic nitrogen at a soil particle size of 0.25~0.5. The models using data dimensionality reduction and those that used the BOSS method to estimate available potassium (R2C = 0.977, R2P = 0.981, RPD = 7.222) and effective phosphorus (R2C = 0.969, R2P = 0.964, RPD = 5.163) had the best accuracy. In order to offer a reference for the accurate detection of soil physicochemical properties in tea plantations, this study investigated the modeling effect of each physicochemical property under various soil particle sizes and integrated the regression model with various downscaling strategies.

Structure-effect relationship studies of polysaccharides based on receptor-active centres: an alternative view.

Polysaccharides are ubiquitous biomolecules found in nature that have attracted research interest due to their unique nutritional and pharmacological value. Their structural variability is the basis for the diversification of their biological functions, but it also increases the difficulty of polysaccharide research. This review proposes a downscaling strategy and corresponding technologies based on the receptor-active centre. Low molecular weight, high purity, and homogeneous active polysaccharide/oligosaccharide fragments (AP/OFs) obtained by a controlled degradation of polysaccharides and graded activity screening will simplify the study of complex polysaccharides. The historical origins of polysaccharide receptor-active centres are summarized, and the principle-verification processes involved in this hypothesis and their implications for practical use are introduced. Successful cases of emerging technologies will be reviewed in detail and the specific hurdles that AP/OFs pose will be discussed. Finally, we will give an outlook on current limitations and possible future applications of receptor-active centres in the field of polysaccharides.