Science Bulletin最新文献

Van der Waals materials hosting Kitaev interactions are promising platforms for exploring exotic quantum phenomena. Here, we report inelastic neutron scattering investigations of the van der Waals antiferromagnet VBr₃, which forms a honeycomb lattice structure at room temperature and exhibits zigzag-type magnetic order below 26.5 K. Our observations reveal distinctive low-energy spin excitations arising from Γ, Γ', and M' points, each featuring a spin gap of around 2.5 meV. The overall spin excitation spectra can be effectively described by a spin Hamiltonian incorporating substantial nearest-neighbor Kitaev and biquadratic interactions, along with Heisenberg interactions. Our findings not only establish VBr₃ as a new Kitaev magnet but also suggest that ligand engineering may provide a promising strategy to modulate Kitaev interactions, offering new opportunities for designing Kitaev materials with tailored quantum properties.

Border areas between neighboring countries are crucial for the national and global success of sustainable development. These regions have witnessed rapid and widespread changes in land cover and use, especially the expansion of impervious surface areas (ISA). However, the global patterns and driving factors for this expansion are not well understood. We investigate ISA expansion in global borderlands by integrating high-frequency time-series satellite data, revealing that ISA has doubled between 1985 and 2020. The expansion is more pronounced in border areas with significant economic income disparities between countries, suggesting an overall attraction effect. Notably, 44 out of 310 borderlands (14%) accounted for 50% of ISA expansion over the past 36 years. Around one-third of global borderlands exhibit border-oriented development tendencies or border-prone characteristics. Our correlation and causation analyses indicate that population growth and topography are the primary drivers, with slight variations across different expansion modes. Understanding these border-prone characteristics and the underlying reasons for ISA expansion provides new empirical insights into urban sprawl, ecological environments, and sustainable development in border areas.

Understanding how flood frequency and its distribution have changed over the Holocene in eastern monsoon China, a densely populated region, is vital for improving risk management and disaster mitigation. However, the spatiotemporal patterns of Holocene floods in this region remain poorly understood. Here, we reconstruct the history of large floods in the middle-lower Yellow River (north) and Yangtze River (south) basins. This provides the first clear evidence of a persistent dipole flooding pattern between these regions, with a ∼1.0 ka cyclicity across the Holocene. Proxy records and climate model simulations indicate that within the monsoon climate regime, increased flooding in the Yangtze River basin aligns with enhanced El Niño events, which are modulated by millennial-scale weakening of the Atlantic Meridional Overturning Circulation (AMOC). Sensitivity simulations further reveal that flooding in the Yellow River basin tends to peak during solar maxima, through modulation of a persistent La Niña-like background state. Our findings suggest that continued AMOC weakening in the future could lead to more intense El Niño events, potentially increasing the flood risk in southern China. This underscores the need to integrate long-term climate dynamics into future adaptation strategies.

Type II-P supernovae (SNeII-P) are the most common class of core-collapse SNe in the local Universe and play critical roles in many aspects of astrophysics. Since decades ago theorists have predicted that SNeII-P may originate not only from single stars but also from interacting binaries. While ∼20 SNII-P progenitors have been directly detected on pre-explosion images, observational evidence still remains scarce for this speculated binary progenitor channel. In this work, we report the discovery of a red supergiant progenitor for the Type II-P SN2018gj. While the progenitor resembles those of other SNeII-P in terms of effective temperature and luminosity, it is located in a very old environment, and SN2018gj has an abnormally short plateau in the light curve. With state-of-the-art binary evolution simulations, we find these characteristics can only be explained if the progenitor of SN2018gj is the merger product of a close binary system, which developed a different interior structure and evolved over a longer timescale compared with single-star evolution. This work provides the first compelling evidence for the long-sought binary progenitor channel toward SNeII-P, and our methodology serves as an innovative and pragmatic tool to motivate further investigations into this previously hidden population of SNeII-P from binaries.

Spatial transcriptomics (ST) has become a key technology for interrogating gene expression within spatial context, providing spatially resolved insights into tissue architecture and microenvironmental organization. Rapid advances in experimental platforms and analytical methods, however, have resulted in challenges for technology selection, methodological comparison, and data interpretation. In this review, we present a systematic summary of 594 ST analysis tools spanning 77 ST technologies (as of September 2025). We outline the complete analytical workflow and discuss major analytical tasks, including data preprocessing, denoising and imputation, spatial pattern and domain identification, cellular composition, trajectory analysis, cell-cell communication, and spatial multi-omics integration. For each task, we summarize representative methodological principles and emphasize platform-dependent considerations arising from differences in spatial resolution and detection efficiency. We further highlight how analytical applications of ST data have enabled biomedical discoveries by revealing spatial heterogeneity, tissue organization, and context-dependent cellular interactions. Furthermore, we develop SpatialToolDB (https://www.spatialtooldb.yelab.site/), a systematically curated, categorized, and continuously updated platform that integrates the ST technologies, analytical methods, and related databases covered in this review, facilitating informed tool selection and method comparison. We also discuss development trends and future directions of spatial-omics technologies and analytical tools, including advances in spatial technologies, AI-driven computation, benchmarking and standardization, and improved experimental validation for mechanistic and predictive spatial biology. Together, this review and SpatialToolDB provide a data-driven foundation for selecting ST platforms and analytical strategies tailored to diverse biological and translational research applications.