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The prevalence of teamwork in contemporary science has raised new questions about collaboration networks and the potential impact on research outcomes. Previous studies primarily focused on pairwise interactions between scientists when constructing collaboration networks, potentially overlooking group interactions among scientists. In this study, we introduce a higher-order network representation using algebraic topology to capture multi-agent interactions, i.e., simplicial complexes. Our main objective is to investigate the influence of higher-order structures in local collaboration networks on the productivity of the focal scientist. Leveraging a dataset comprising more than 3.7 million scientists from the Microsoft Academic Graph, we uncover several intriguing findings. Firstly, we observe an inverted U-shaped relationship between the number of disconnected components in the local collaboration network and scientific productivity. Secondly, there is a positive association between the presence of higher-order loops and individual scientific productivity, indicating the intriguing role of higher-order structures in advancing science. Thirdly, these effects hold across various scientific domains and scientists with different impacts, suggesting strong generalizability of our findings. The findings highlight the role of higher-order loops in shaping the development of individual scientists, thus may have implications for nurturing scientific talent and promoting innovative breakthroughs.

Based on dynamic monitoring data on China’s population, by using complex networks, spatial analysis and mathematical measurement, this study reveals the spatial characteristics and influencing factors of the network of flows of highly educated talents in the Yangtze River Delta region from the national and local perspectives. In the two perspectives, the network has strong isomorphism and certain differences. The in-flow of highly educated talents from cities with high administrative levels and more developed economies to Shanghai constitutes the core of the entire network. From a national perspective, highly educated talents tend to converge to the Yangtze River Delta region. From a local perspective, it was found that these talents cluster towards a limited number of cities in the region. From both perspectives, the flow network has developed into a “core-periphery” progressive hierarchical structure, with Shanghai becoming the sole core city. There is little difference in the influencing factors of talent mobility from both macro and meso perspectives. Highly educated talents would frequently flow between cities with strong economic development levels, and cities with high education level, scientific and technological level, complete infrastructure, and good aesthetics. However, geographical distance still plays a hindering role in the flow of highly educated talents, and factors such as cultural identity, institutional, and social modality differences among regions also have a certain effect on the flow of these talents.

In order to improve the performance of fiber sensors and fully tap the potential of optical fiber sensors, various optical materials have been selectively coated on optical fiber sensors under the background of the rapid development of various optical materials. On the basis of retaining the original characteristics of the optical fiber sensors, the coated sensors are endowed with new characteristics, such as high sensitivity, strong structure, and specific recognition. Many materials with a large thermal optical coefficient and thermal expansion coefficients are applied to optical fibers, and the temperature sensitivities are improved several times after coating. At the same time, fiber sensors have more intelligent sensing capabilities when coated with specific recognition materials. The same/different kinds of materials combined with the same/different fiber structures can produce different measurements, which is interesting. This paper summarizes and compares the fiber sensors treated by different coating materials.

Cell mass and chemical composition are important aggregate cellular properties that are especially relevant to physiological processes, such as growth control and tissue homeostasis. Despite their importance, it has been difficult to measure these features quantitatively at the individual cell level in intact tissue. Here, we introduce normalized Raman imaging (NoRI), a stimulated Raman scattering (SRS) microscopy method that provides the local concentrations of protein, lipid, and water from live or fixed tissue samples with high spatial resolution. Using NoRI, we demonstrate that protein, lipid, and water concentrations at the single cell are maintained in a tight range in cells under the same physiological conditions and are altered in different physiological states, such as cell cycle stages, attachment to substrates of different stiffness, or by entering senescence. In animal tissues, protein and lipid concentration varies with cell types, yet an unexpected cell-to-cell heterogeneity was found in cerebellar Purkinje cells. The protein and lipid concentration profile provides means to quantitatively compare disease-related pathology, as demonstrated using models of Alzheimer’s disease. This demonstration shows that NoRI is a broadly applicable technique for probing the biological regulation of protein mass, lipid mass, and water mass for studies of cellular and tissue growth, homeostasis, and disease.

G-protein gamma subunit 2 (GNG2) plays a vital role in various cellular processes, yet its specific function in colorectal cancer (CRC), particularly in highly invasive cases and brain metastasis, remains unclear. This study identifies GNG2 as a key regulator in metastatic colorectal cancer (mCRC) through bioinformatics analysis and experimental validation. Functional enrichment analyses reveal that GNG2 is related to the PI3K/AKT/mTOR signaling pathway and cell cycle regulation. These findings were further confirmed by in vitro and in vivo experiments. The overexpression of GNG2 significantly induced G0/G1 arrest and further inhibited the PI3K/AKT/mTOR axis in CRC cell lines, including suppressed proliferation, migration, and invasion and metastasis ability. In vivo studies using an orthotopic xenograft model demonstrated that GNG2 overexpression reduced brain metastasis and extended overall survival in mice. Immunohistochemistry and multiplex immunofluorescence confirmed the association between GNG2 overexpression, the PI3K/AKT/mTOR signaling pathway, and G0/G1 arrest. Our study suggests that GNG2 contributes to tumor suppression in CRC, particularly in preventing brain metastasis, and could serve as a promising biomarker and treatment target for mCRC, offering fresh insights into the molecular processes driving cancer progression and metastasis.

As the core component of an engine, the vibration characteristics of blades directly affect the stability and lifespan of the engine. Thus, monitoring the vibration status of the blades is essential. This paper presents an improvement on the blade tip timing (BTT) method based on Composite Reference. The conventional BTT method, when computing blade vibration displacement, typically presumes a constant rotor speed per revolution, which fails to account for the rotor’s instantaneous state conditions accurately. In this study, the state space equations for the rotor’s instantaneous angular velocity and position are derived and solved via a Kalman filter to rectify the rotor’s instantaneous speed. Furthermore, the composite reference method is improved by using the multi-sensor straight line fitting (SLF) method of all sensors, enhancing the precision of blade vibration displacement identification. The efficacy of this approach has been validated through simulation experiments.

This study aimed to investigate the anti-osteoporotic mechanisms of naringin in osteoblasts and mice. In vitro, MC3T3-E1 cells were treated with naringin to detect cell proliferation, alkaline phosphatase (ALP) activity, and calcified nodule formation. Western blot was used to analyze the expression of osteogenic markers (OPN, COL1A1, RUNX2) and Wnt/β-catenin pathway proteins (Wnt3a, β-catenin). In vivo, ovariectomized (OVX) mice were treated with naringin for 3 months to observe bone microstructure, femoral histomorphology, and marker expression. Results showed that 0.1, 0.5, and 1 µmol/L naringin significantly promoted cell proliferation, enhanced ALP activity, and increased calcified nodule formation. Naringin also improved bone mineral density (BMD) and trabecular bone number in OVX mice. It elevated serum levels of bone formation markers (P1NP, OCN) while reducing the bone resorption marker CTX-1. Both in vitro and in vivo, naringin upregulated OPN, COL1A1, RUNX2, Wnt3a, and β-catenin expression, and induced β-catenin nuclear translocation. Notably, naringin antagonized the inhibitory effects of XAV939 (a Wnt/β-catenin pathway inhibitor) on OPN, COL1A1, and RUNX2 protein expression. These findings demonstrate that naringin enhances bone density in OVX mice and promotes osteogenic differentiation of MC3T3-E1 cells via activation of the Wnt/β-catenin pathway.

Ultrastrong and deep-strong coupling are two coupling regimes rich in intriguing physical phenomena. Recently, hybrid magnonic systems have emerged as promising candidates for exploring these regimes, owing to their unique advantages in quantum engineering. However, because of the relatively weak coupling between magnons and other quasiparticles, ultrastrong coupling is predominantly realized at cryogenic temperatures, while deep-strong coupling remains to be explored. In our work, we achieve both theoretical and experimental realization of room-temperature ultrastrong magnon-magnon coupling in synthetic antiferromagnets with intrinsic asymmetry of magnetic anisotropy. Unlike most ultrastrong coupling systems, where the counter-rotating coupling strength g 2 is strictly equal to the co-rotating coupling strength g 1 , our systems allow for highly tunable g 1 and g 2 . This high degree of freedom also enables the realization of normalized g 1 or g 2 larger than 0.5. Particularly, our experimental findings reveal that the maximum observed g 1 is nearly identical to the bare frequency, with g 1 / ω 0  = 0.963, indicating a close realization of deep-strong coupling within our hybrid magnonic systems. Our results highlight synthetic antiferromagnets as platforms for exploring unconventional ultrastrong and even deep-strong coupling regimes, facilitating the further exploration of quantum phenomena. Deep-strong coupling in hybrid magnonic systems is yet to be explored. Here, the authors unveil unconventional coupling properties in synthetic antiferromagnets. The systems’ high degree of freedom enables a near-realization of deep-strong coupling.

Osteoarthritis (OA) is the most prevalent degenerative joint disease, characterized by cartilage degradation, chondrocyte apoptosis, synovial inflammation, and subchondral bone remodeling. Accumulating evidence highlights the central role of heat shock proteins (HSPs) in OA pathogenesis and progression. HSPs function as molecular chaperones that maintain proteostasis by facilitating protein folding, preventing aggregation, and modulating stress responses. Dysregulated expression of HSP27, HSP40, HSP60, HSP70, HSP90, and GRP78 contributes to inflammation, extracellular matrix breakdown, and chondrocyte apoptosis, but also provides cytoprotective effects under certain conditions. This duality positions HSPs as both biomarkers of disease activity and promising therapeutic targets. Here, we comprehensively review the roles of HSPs in regulating apoptosis, autophagy, and inflammatory signaling in OA. We further discuss emerging therapeutic strategies that modulate HSP expression or activity, including synthetic drugs, natural products, nanomedicine, stem cell therapy, physical modalities (heat, ultrasound, phototherapy, microwaves), and biological agents such as monoclonal antibodies. By integrating mechanistic insights and translational advances, this review underscores the potential of HSP-targeted therapies to preserve chondrocyte function, maintain extracellular matrix integrity, and slow OA progression, paving the way for novel disease-modifying interventions.

In this paper, the impact jet field between the pneumatic nozzle and the workpiece surface is simulated by the computational fluid dynamics method, and the influence law of the nozzle structure parameters on the jet performance is obtained by combining the response surface method (RSM), so as to improve the dust removal effect of the pneumatic nozzle. Firstly, the nozzle impact jet field calculation model was established, and the experimental platform of wind speed and volume measurement was built to verify the accuracy of the numerical calculation model and to simulate and analyze the jet field distribution characteristics of the nozzle under rotating working conditions. Then combined with the Box-Behnken Design (BBD) method, a response surface regression model with nozzle inlet radius (R1), cylindrical section length (L), and cone angle (A) as design variables and nozzle jet fixed point (20 mm) flow rate as the target variable was established to find the optimal combination of nozzle characteristics parameters. The results show that the optimized nozzle characteristics parameters using RSM can effectively improve the nozzle jet performance, the optimized jet flow rate increased by 8.38%, and can be more effective in dust removal; jet pressure on the workpiece surface decreases as the nozzle incidence angle increases; in the speed range of 400–1200 r/min, the pressure change caused by the jet on the wall surface is small, and the flow rate is relatively stable.